Kod wyliczający wykorzystane biblioteki.
#devtools::install_github("tidyverse/readr")
library(readr)
#devtools::install_github("hadley/dplyr")
library(dplyr)
#devtools::install_github("ropensci/plotly")
library(plotly)
#devtools::install_github("tidyverse/ggplot2")
library(ggplot2)
#devtools::install_github("topepo/caret/pkg/caret")
library(caret)
#devtools::install_github("haozhu233/kableExtra")
library(kableExtra)
#devtools::install_github("tidyverse/magrittr")
library(magrittr)
#Paczki do caret :
#install.packages("randomForest")
#library(randomForest)
#install.packages("e1071")
#library(e1071)
Kod zapewniający powtarzalność wyników przy każdym uruchomieniu raportu na tych samych danych.
set.seed(2157)
Kod pozwalający wczytać dane z pliku.
all_summary <- read_delim("all_summary.csv", delim = ";", trim_ws = TRUE, comment = "")
Kod usuwający z danych wiersze posiadające dane wartość zmiennej res_name.
to_remove = c('UNK', 'UNX', 'UNL', 'DUM', 'N', 'BLOB', 'ALA', 'ARG', 'ASN', 'ASP', 'CYS', 'GLN', 'GLU', 'GLY', 'HIS', 'ILE', 'LEU', 'LYS', 'MET', 'MSE', 'PHE', 'PRO', 'SEC', 'SER', 'THR', 'TRP', 'TYR', 'VAL', 'DA', 'DG', 'DT', 'DC', 'DU', 'A', 'G', 'T', 'C', 'U', 'HOH', 'H20', 'WAT')
all_summary %<>% filter(!(res_name %in% to_remove))
Kod przetwarzający brakujące dane.
all_summary %<>% filter(!is.na(res_name))
Sekcja podsumowująca rozmiar zbioru i podstawowe statystyki
Liczba kolumn
ncol(all_summary)
## [1] 412
Liczba wierszy
nrow(all_summary)
## [1] 591042
kable(t(do.call(cbind,lapply(all_summary, summary)))) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>%
scroll_box(width = "100%", height = "600px")
| Min. | 1st Qu. | Median | Mean | 3rd Qu. | Max. | NA’s | |
|---|---|---|---|---|---|---|---|
| blob_coverage | 575726 | character | character | 575726 | character | character | 575726 |
| res_coverage | 575726 | character | character | 575726 | character | character | 575726 |
| title | 575726 | character | character | 575726 | character | character | 575726 |
| pdb_code | 575726 | character | character | 575726 | character | character | 575726 |
| res_name | 575726 | character | character | 575726 | character | character | 575726 |
| res_id | -62 | 301 | 501 | 779.011967757066 | 999 | 9999 | 96 |
| chain_id | 575726 | character | character | 575726 | character | character | 575726 |
| blob_volume_coverage | 0.02004008016 | 0.504122352125 | 0.728749034 | 0.669962213490053 | 0.8703854008 | 1 | 0.02004008016 |
| blob_volume_coverage_second | 0 | 0 | 0 | 0.0193655752498971 | 0 | 0.9988751406 | 0 |
| res_volume_coverage | 0.001883948757 | 0.24625367585 | 0.4570532077 | 0.495926068892134 | 0.705417299775 | 1 | 0.001883948757 |
| res_volume_coverage_second | 0 | 0 | 0 | 0.06658263737737 | 0 | 1 | 0 |
| local_res_atom_count | 1 | 4 | 6 | 14.1170278917402 | 20 | 178 | 1 |
| local_res_atom_non_h_count | 1 | 4 | 6 | 13.7714537818337 | 20 | 111 | 1 |
| local_res_atom_non_h_occupancy_sum | -7.38 | 4 | 6 | 13.3183036461789 | 18.65 | 111 | -7.38 |
| local_res_atom_non_h_electron_sum | 3 | 30 | 52 | 102.040731181152 | 137 | 1848 | 3 |
| local_res_atom_non_h_electron_occupancy_sum | -45.91 | 29 | 48 | 97.9419663451017 | 129 | 858 | -45.91 |
| local_res_atom_C_count | 0 | 0 | 3 | 7.90501210645342 | 10 | 84 | 0 |
| local_res_atom_N_count | 0 | 0 | 0 | 1.21496336799102 | 1 | 28 | 0 |
| local_res_atom_O_count | 0 | 1 | 3 | 3.84094517183521 | 5 | 61 | 0 |
| local_res_atom_S_count | 0 | 0 | 0 | 0.22136050829735 | 0 | 13 | 0 |
| dict_atom_non_h_count | 1 | 4 | 6 | 14.1079280137555 | 20 | 128 | 11007 |
| dict_atom_non_h_electron_sum | 3 | 30 | 50 | 104.522504112665 | 138 | 1223 | 11007 |
| dict_atom_C_count | 0 | 0 | 3 | 8.05252169663142 | 10 | 93 | 11007 |
| dict_atom_N_count | 0 | 0 | 0 | 1.19241250958441 | 1 | 28 | 11007 |
| dict_atom_O_count | 0 | 1 | 3 | 4.05049591035542 | 6 | 55 | 11007 |
| dict_atom_S_count | 0 | 0 | 0 | 0.220739872396714 | 0 | 13 | 11007 |
| skeleton_data | 575726 | character | character | 575726 | character | character | 575726 |
| skeleton_cycle_4 | 0 | 0 | 0 | 0.372863132809705 | 0 | 2792 | 0 |
| skeleton_diameter | 0 | 2 | 13 | 24.4203110507429 | 33 | 671 | 0 |
| skeleton_cycle_6 | 0 | 0 | 0 | 0.0127751743016643 | 0 | 150 | 0 |
| skeleton_cycle_7 | 0 | 0 | 0 | 0.00427112897454692 | 0 | 54 | 0 |
| skeleton_closeness_006_008 | 0 | 0 | 0 | 2.61396740810733 | 0 | 417 | 0 |
| skeleton_closeness_002_004 | 0 | 0 | 0 | 0.0853513650590733 | 0 | 907 | 0 |
| skeleton_cycle_3 | 0 | 0 | 0 | 0.0562194516141359 | 0 | 957 | 0 |
| skeleton_avg_degree | 0 | 1.333333333 | 1.875 | 1.57384315293755 | 1.962962963 | 6.458598726 | 0 |
| skeleton_closeness_004_006 | 0 | 0 | 0 | 0.945828397536328 | 0 | 492 | 0 |
| skeleton_closeness_010_012 | 0 | 0 | 0 | 3.52082240510243 | 0 | 779 | 0 |
| skeleton_closeness_012_014 | 0 | 0 | 0 | 3.27787523926312 | 0 | 2579 | 0 |
| skeleton_edges | 0 | 2 | 14 | 35.8367313617936 | 40 | 9934 | 0 |
| skeleton_radius | 0 | 1 | 7 | 12.5078370613799 | 17 | 336 | 0 |
| skeleton_cycle_8_plus | 0 | 0 | 0 | 0.190852940461261 | 0 | 1863 | 0 |
| skeleton_closeness_020_030 | 0 | 0 | 0 | 5.31210332692982 | 1 | 1009 | 0 |
| skeleton_deg_5_plus | 0 | 0 | 0 | 0.148687049047637 | 0 | 2998 | 0 |
| skeleton_closeness_016_018 | 0 | 0 | 0 | 2.25168917158509 | 0 | 434 | 0 |
| skeleton_closeness_008_010 | 0 | 0 | 0 | 3.5107273251512 | 0 | 304 | 0 |
| skeleton_closeness_018_020 | 0 | 0 | 0 | 1.75372312523666 | 0 | 569 | 0 |
| skeleton_average_clustering | 0 | 0 | 0 | 0.00012396244422612 | 0 | 0.4666666667 | 0 |
| skeleton_closeness_040_050 | 0 | 0 | 0 | 1.83978316073966 | 1 | 572 | 0 |
| skeleton_closeness_014_016 | 0 | 0 | 0 | 2.85511858071374 | 0 | 129 | 0 |
| skeleton_center | 1 | 1 | 1 | 1.6184278632544 | 2 | 251 | 1 |
| skeleton_closeness_000_002 | 0 | 0 | 0 | 0.112369425733769 | 0 | 204 | 0 |
| skeleton_density | 0 | 0.02571785268 | 0.09090909091 | 0.218411095861248 | 0.25 | 1 | 0 |
| skeleton_closeness_030_040 | 0 | 0 | 0 | 2.83986827067042 | 1 | 864 | 0 |
| skeleton_deg_4 | 0 | 0 | 0 | 0.120800519691659 | 0 | 228 | 0 |
| skeleton_deg_0 | 0 | 0 | 0 | 0.111071933523933 | 0 | 1 | 0 |
| skeleton_deg_1 | 0 | 2 | 2 | 3.24242087381845 | 3 | 85 | 0 |
| skeleton_deg_2 | 0 | 1 | 12 | 30.5136366952335 | 35 | 877 | 0 |
| skeleton_deg_3 | 0 | 0 | 0 | 2.00964695011168 | 2 | 157 | 0 |
| skeleton_graph_clique_number | 1 | 2 | 2 | 1.89525572928789 | 2 | 5 | 1 |
| skeleton_nodes | 1 | 3 | 15 | 36.1462640214269 | 41 | 3801 | 1 |
| skeleton_cycles | 0 | 0 | 0 | 0.690467340366772 | 0 | 6134 | 0 |
| skeleton_cycle_5 | 0 | 0 | 0 | 0.0534855122054589 | 0 | 320 | 0 |
| skeleton_closeness_050_plus | 0 | 0 | 3 | 5.22703681959821 | 11 | 310 | 0 |
| skeleton_periphery | 1 | 2 | 2 | 2.00518649496462 | 2 | 101 | 1 |
| local_volume | 49.248 | 212.976 | 347.2 | 861.32750772416 | 797.04 | 90952.512 | 49.248 |
| local_electrons | 0.01170493793 | 3.45070153825 | 7.851201172 | 17.828009979626 | 19.90227051 | 442.4445 | 0.01170493793 |
| local_mean | 0.000114725 | 0.012078 | 0.01859395 | 0.0235338288678278 | 0.0285545 | 0.426442 | 0.000114725 |
| local_std | 0.000660591 | 0.06827275 | 0.09843535 | 0.122630826234582 | 0.143231 | 1.95956 | 0.000660591 |
| local_min | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| local_max | 0.0045201 | 0.5650945 | 0.888857 | 1.35413959116681 | 1.50644 | 44.6336 | 0.0045201 |
| local_max_over_std | 2.836182117 | 5.23372314075 | 7.2410710645 | 9.76688605021531 | 11.2927055825 | 173.2519886 | 2.836182117 |
| local_skewness | 0.001174014706 | 0.120711275325 | 0.17421898725 | 0.222862932953116 | 0.25619059375 | 4.035154736 | 0.001174014706 |
| local_cut_by_mainchain_volume | 0 | 0 | 0 | 0.365240562350841 | 0.024 | 53.504 | 0 |
| local_near_cut_count_C | 0 | 0 | 2 | 4.38413933016748 | 6 | 163 | 0 |
| local_near_cut_count_other | 0 | 0 | 0 | 0.0121602984753164 | 0 | 14 | 0 |
| local_near_cut_count_S | 0 | 0 | 0 | 0.123291287869577 | 0 | 15 | 0 |
| local_near_cut_count_O | 0 | 0 | 1 | 2.0936695580884 | 3 | 76 | 0 |
| local_near_cut_count_N | 0 | 0 | 1 | 2.16578546044473 | 3 | 41 | 0 |
| part_00_shape_segments_count | 0 | 5 | 25 | 340.913674213081 | 144 | 114577 | 0 |
| part_00_density_segments_count | 0 | 5 | 25 | 340.913674213081 | 144 | 114577 | 0 |
| part_00_volume | 0 | 6.856 | 14.328 | 33.1335366893279 | 34.872 | 2427.944 | 0 |
| part_00_electrons | 0 | 3.4324799905 | 7.783738288 | 17.6294861845862 | 19.3093905375 | 441.1374407 | 0 |
| part_00_mean | 0 | 0.363105079825 | 0.51463737475 | 0.60170541369399 | 0.717429216975 | 8.596871096 | 0 |
| part_00_std | 0 | 0.064236985965 | 0.1210435661 | 0.209551866773866 | 0.23328975395 | 8.010635794 | 0 |
| part_00_max | 0 | 0.56509415805 | 0.8888492286 | 1.35413509828394 | 1.506440222 | 44.63356781 | 0 |
| part_00_max_over_std | 0 | 5.23370953075 | 7.2410710645 | 9.766839548402 | 11.2927055825 | 173.2519886 | 0 |
| part_00_skewness | 0 | 0.05595256506 | 0.11086069425 | 0.215817126759591 | 0.23349291195 | 10.50955383 | 2 |
| part_00_parts | 0 | 1 | 1 | 1.07092783720033 | 1 | 28 | 0 |
| part_00_shape_O3 | 121.3947368 | 27057.0207475 | 97222.576165 | 1695479.56498225 | 608579.833125 | 2628816578 | 6 |
| part_00_shape_O4 | 3807.052632 | 181656262.075 | 2333791302 | 10797740453895.3 | 76345986842.5 | 4.338385464e+17 | 6 |
| part_00_shape_O5 | 33777.02632 | 337713238000 | 15383126150000 | 1.81500729804873e+20 | 2266284574500000 | 2.908411654e+25 | 6 |
| part_00_shape_FL | 75.70408004 | 916394745.875 | 39080558925 | 62327442959780432 | 5624132323500 | 8.380412043e+21 | 6 |
| part_00_shape_O3_norm | 0.2305739889 | 0.270932235625 | 0.38348836015 | 0.494452362404451 | 0.6108486294 | 39.64691261 | 6 |
| part_00_shape_O4_norm | 0.01756274188 | 0.0217118341525 | 0.03388987025 | 0.0618813374712343 | 0.06955462012 | 6.010881387 | 6 |
| part_00_shape_O5_norm | 0.0004262883158 | 0.000513124528 | 0.0007722045561 | 0.00199060865767354 | 0.00176993665425 | 0.4110453704 | 6 |
| part_00_shape_FL_norm | 1.134335211e-07 | 0.00063401688275 | 0.0056627527875 | 0.0568302783374848 | 0.0321326354675 | 189.3506959 | 6 |
| part_00_shape_I1 | 479.8371004 | 1194049.1195 | 7855760.194 | 3000624917.82367 | 135109135.55 | 163322206500000 | 6 |
| part_00_shape_I2 | 56939.7087 | 219066700525 | 9063620757500 | 2.96404467406671e+20 | 2084935175750000 | 3.58305756e+25 | 6 |
| part_00_shape_I3 | 49989.15888 | 529484036050 | 25210998480000 | 8.69401592072794e+22 | 9158165266250000 | 2.665214001e+28 | 6 |
| part_00_shape_I4 | 42.46570174 | 467420883.275 | 21415867520 | 35090178451447548 | 3380179159000 | 4.526597788e+21 | 6 |
| part_00_shape_I5 | 2.451835149 | 72011194.6475 | 6438371323 | 16932002111629766 | 1430157044750 | 1.957388285e+21 | 6 |
| part_00_shape_I6 | 22342.79801 | 14397295055 | 347048438700 | 1680470065959411968 | 42027035162500 | 3.743293967e+23 | 6 |
| part_00_shape_I1_norm | 0.06322810516 | 0.099123468235 | 0.23224509785 | 0.55832827200875 | 0.597536216825 | 2760.572581 | 6 |
| part_00_shape_I2_norm | 0.001040183787 | 0.00195449720925 | 0.006747190324 | 0.0911755011626962 | 0.035455551735 | 303.9073125 | 6 |
| part_00_shape_I3_norm | 0.0008016258967 | 0.00313897274 | 0.02540066147 | 31.3744237593425 | 0.198875116775 | 7617375.322 | 6 |
| part_00_shape_I4_norm | 4.590246527e-08 | 0.000293604645125 | 0.0031912351115 | 0.0387685575170504 | 0.0198827000175 | 189.0716741 | 6 |
| part_00_shape_I5_norm | 1.433670721e-10 | 4.18361131125e-05 | 0.0010844612885 | 0.0267274103034399 | 0.00966937123725 | 188.8856596 | 6 |
| part_00_shape_I6_norm | 0.004862942323 | 0.0107157755525 | 0.043569366905 | 0.86694327376586 | 0.198634037575 | 109414.6959 | 6 |
| part_00_shape_M000 | 38 | 857 | 1791 | 4141.7352497742 | 4359 | 303493 | 6 |
| part_00_shape_CI | -129.4545845 | -0.79430445765 | 0.0002969493295 | 0.0461305970679179 | 0.84061899865 | 70.04395863 | 6 |
| part_00_shape_E3_E1 | 6.638587028e-05 | 0.0864778723025 | 0.17003142535 | 0.24235343864368 | 0.35560261055 | 0.9947771112 | 6 |
| part_00_shape_E2_E1 | 0.000128514727 | 0.215891090125 | 0.3819474389 | 0.423876545882786 | 0.614735544825 | 1 | 6 |
| part_00_shape_E3_E2 | 0.01144195139 | 0.36984490035 | 0.57076422825 | 0.552831054820276 | 0.7423507087 | 1 | 6 |
| part_00_shape_sqrt_E1 | 1.076346776 | 4.03505970775 | 5.892465523 | 8.05604991703898 | 10.0915915 | 202.7615055 | 6 |
| part_00_shape_sqrt_E2 | 0.738902385 | 2.597322666 | 3.518080126 | 4.44354458691352 | 5.26993273625 | 34.51639297 | 6 |
| part_00_shape_sqrt_E3 | 0.5959134156 | 1.9530732195 | 2.5897241265 | 2.94632383341524 | 3.47936533475 | 20.34264666 | 6 |
| part_00_density_O3 | 9.711224684 | 13005.5724725 | 47560.76906 | 801019.914185333 | 268997.705975 | 567372596.1 | 6 |
| part_00_density_O4 | 24.38308404 | 41663209.8325 | 561109355.8 | 1363855549730.82 | 14706761645 | 2.005882204e+16 | 6 |
| part_00_density_O5 | 17.32080844 | 36960799762.5 | 1803784086500 | 1746409063047778560 | 189727098050000 | 1.807558764e+23 | 6 |
| part_00_density_FL | -3.009896981 | 172450124.6 | 8607309656 | 3734748385523714 | 1178770349500 | 4.048898964e+20 | 6 |
| part_00_density_O3_norm | 0.03559376981 | 0.3846557317 | 0.6088333939 | 0.751393069472097 | 0.96385940315 | 412.328286 | 6 |
| part_00_density_O4_norm | 0.0004207922565 | 0.04164163407 | 0.08846415947 | 0.147616610196422 | 0.18082061785 | 32.92661752 | 6 |
| part_00_density_O5_norm | 1.652895249e-06 | 0.0012633898925 | 0.00322639427 | 0.0078284383686351 | 0.00782691997625 | 27.99506456 | 6 |
| part_00_density_FL_norm | -0.03476061339 | 0.00201224585825 | 0.018983227155 | 0.347878948297929 | 0.12975471975 | 29271.04832 | 6 |
| part_00_density_I1 | 42.2229442 | 547754.671375 | 3484281.7855 | 1051219473.27715 | 58344659.085 | 12820833470000 | 6 |
| part_00_density_I2 | 363.0952973 | 45546422817.5 | 1797947969000 | 13843497090749585408 | 3.74152866e+14 | 1.508584529e+24 | 6 |
| part_00_density_I3 | 503.5110024 | 112113904625 | 4966128197000 | 1.00083653298471e+21 | 1758885410750000 | 1.642551475e+26 | 6 |
| part_00_density_I4 | -1.005383674 | 92055091.6875 | 5189857717.5 | 2248578330649368 | 790615926800 | 2.341519885e+20 | 6 |
| part_00_density_I5 | 0.03176528962 | 19916881.06 | 2029519085 | 1257798293952136 | 411220406000 | 1.203267165e+20 | 6 |
| part_00_density_I6 | 182.7383907 | 3168079696 | 73302795715 | 40942961992870536 | 8197618476750 | 5.254844754e+21 | 6 |
| part_00_density_I1_norm | 0.001747813076 | 0.218069055275 | 0.5819320415 | 2.44445273171427 | 1.538936734 | 298590.9488 | 6 |
| part_00_density_I2_norm | 8.053167968e-07 | 0.00884582893425 | 0.046127570835 | 0.749308558824666 | 0.242191741325 | 7616.408967 | 6 |
| part_00_density_I3_norm | 6.251427124e-07 | 0.015648092145 | 0.1517720267 | 179056.280189339 | 1.31012996425 | 89117182130 | 6 |
| part_00_density_I4_norm | -0.01161094662 | 0.0010091733 | 0.011509753725 | 0.279274932530713 | 0.0865742033125 | 29231.84652 | 6 |
| part_00_density_I5_norm | 1.637856779e-10 | 0.0001977232373 | 0.0048093909295 | 0.233538922006994 | 0.049697683875 | 29205.71198 | 6 |
| part_00_density_I6_norm | 2.090698844e-05 | 0.034241724925 | 0.16769547215 | 296.843746955821 | 0.7961212752 | 123080053.3 | 6 |
| part_00_density_M000 | 1.864285111 | 429.0678462 | 972.9981363 | 2203.7087392988 | 2413.69359325 | 55142.18009 | 6 |
| part_00_density_CI | -155.701412 | -0.858521445575 | 0.00019182554265 | 0.0475445073795394 | 0.903993823875 | 89.96053361 | 6 |
| part_00_density_E3_E1 | 6.604160143e-05 | 0.08309210098 | 0.16864460925 | 0.24508064974345 | 0.36542509365 | 0.9958993203 | 6 |
| part_00_density_E2_E1 | 0.0001276943492 | 0.211137407875 | 0.3819973684 | 0.423951283523217 | 0.619479032825 | 0.9999998643 | 6 |
| part_00_density_E3_E2 | 0.01305281121 | 0.3687294446 | 0.57491832355 | 0.554827419624812 | 0.74782409465 | 0.9999999613 | 6 |
| part_00_density_sqrt_E1 | 1.072152367 | 3.7699128855 | 5.573238223 | 7.73700324469222 | 9.76148380475 | 202.4822866 | 6 |
| part_00_density_sqrt_E2 | 0.7382289477 | 2.45726224425 | 3.2819451615 | 4.21820399021366 | 4.98578883075 | 32.97918301 | 6 |
| part_00_density_sqrt_E3 | 0.5954518305 | 1.86961842875 | 2.4330287475 | 2.78243633755072 | 3.24031132325 | 19.37849776 | 6 |
| part_00_shape_Z_7_3 | 6.30312003 | 15.6230944375 | 26.71808221 | 41.1237462309464 | 53.5526852575 | 558.7070258 | 6 |
| part_00_shape_Z_0_0 | 3.011948166 | 14.30362469 | 20.6777599 | 26.2662245907247 | 32.25886848 | 269.172095 | 6 |
| part_00_shape_Z_7_0 | 0.6818404009 | 6.50426107825 | 10.213001845 | 17.4144565952786 | 22.1540931025 | 366.9916795 | 6 |
| part_00_shape_Z_7_1 | 3.661825436 | 9.957970248 | 17.669219445 | 28.2555942748209 | 37.0077526775 | 446.1359298 | 6 |
| part_00_shape_Z_3_0 | 0.571422094 | 5.99214178525 | 10.70816582 | 15.1108089527818 | 19.63898586 | 208.1280084 | 6 |
| part_00_shape_Z_5_2 | 4.580256005 | 14.715472825 | 24.82553103 | 35.0866284669985 | 45.298087505 | 455.101189 | 6 |
| part_00_shape_Z_6_1 | 1.807757938 | 12.040449195 | 20.946944805 | 31.812024920542 | 42.408123735 | 476.2128169 | 6 |
| part_00_shape_Z_3_1 | 2.505837245 | 11.3511645375 | 18.144064605 | 24.4783464264835 | 30.90780641 | 297.2757961 | 6 |
| part_00_shape_Z_6_0 | 0.02436425529 | 5.50200848575 | 9.9224029715 | 14.8506736545214 | 19.27195294 | 299.0132519 | 6 |
| part_00_shape_Z_2_1 | 2.429600076 | 19.40950579 | 28.78839488 | 38.4147364562564 | 48.2438118075 | 420.8093352 | 6 |
| part_00_shape_Z_6_3 | 4.113508963 | 18.75763798 | 31.270307195 | 46.6883901055614 | 61.35824783 | 608.4310162 | 6 |
| part_00_shape_Z_2_0 | 1.049642044 | 14.37872129 | 21.86555755 | 28.2164785088653 | 35.548141675 | 326.5258558 | 6 |
| part_00_shape_Z_6_2 | 2.941402487 | 16.4335561575 | 28.025620615 | 42.1698856754525 | 55.767869235 | 562.2021526 | 6 |
| part_00_shape_Z_5_0 | 0.7928716828 | 5.63076741125 | 12.25827021 | 18.341775594047 | 24.4667285 | 315.573314 | 6 |
| part_00_shape_Z_5_1 | 3.463939546 | 11.5003167725 | 20.557661095 | 29.0088948845917 | 37.8237976825 | 407.4940969 | 6 |
| part_00_shape_Z_4_2 | 3.536957069 | 19.2395184775 | 31.432084135 | 43.9385813428476 | 57.058548525 | 534.4743816 | 6 |
| part_00_shape_Z_1_0 | 0.7373045028 | 1.26192610125 | 1.404309371 | 1.42541623162108 | 1.5670765735 | 2.525211314 | 6 |
| part_00_shape_Z_4_1 | 1.94972829 | 16.0527778625 | 27.07137287 | 37.8083117458604 | 49.7330362975 | 465.6008098 | 6 |
| part_00_shape_Z_7_2 | 5.741843786 | 13.277177295 | 23.42865461 | 36.5547716038074 | 47.899136875 | 530.3215832 | 6 |
| part_00_shape_Z_4_0 | 0.02954763925 | 8.232657805 | 14.91412993 | 20.5455788797275 | 27.39525068 | 313.0934259 | 6 |
| part_00_density_Z_7_3 | 2.894867781 | 10.686300995 | 19.57205548 | 30.4553825486114 | 39.50216056 | 211.1186257 | 6 |
| part_00_density_Z_0_0 | 0.6671321355 | 10.1208894325 | 15.24093811 | 19.1328271408767 | 24.00472661 | 114.7354601 | 6 |
| part_00_density_Z_7_0 | 0.9849014403 | 5.983010466 | 8.579471565 | 14.9279220846135 | 19.0133855125 | 126.9187798 | 6 |
| part_00_density_Z_7_1 | 2.877502984 | 7.48929576825 | 14.0335003 | 22.4186491071828 | 29.3099305175 | 159.9190948 | 6 |
| part_00_density_Z_3_0 | 0.4221085286 | 4.43414719825 | 7.809777715 | 11.3500855817079 | 14.557800735 | 88.53859908 | 6 |
| part_00_density_Z_5_2 | 2.150798646 | 10.02689568 | 17.84693627 | 25.6458810018479 | 33.302145775 | 182.1829673 | 6 |
| part_00_density_Z_6_1 | 0.4343871441 | 7.65719229 | 17.233605405 | 24.8344567149988 | 33.8130627575 | 196.0674613 | 6 |
| part_00_density_Z_3_1 | 1.444641718 | 7.57215946425 | 12.517145155 | 17.3706916024529 | 22.06254339 | 120.8635572 | 6 |
| part_00_density_Z_6_0 | 0.007071927991 | 3.59944586175 | 8.1019986195 | 12.5949888289052 | 17.26946858 | 122.4933814 | 6 |
| part_00_density_Z_2_1 | 0.7737221038 | 14.2676430725 | 21.574873275 | 28.1465605955064 | 34.981755755 | 176.3804765 | 6 |
| part_00_density_Z_6_3 | 0.5448886683 | 12.1694018375 | 23.670134555 | 34.4019352482212 | 45.4517455925 | 282.8048412 | 6 |
| part_00_density_Z_2_0 | 0.3606986122 | 10.98726405 | 17.057697155 | 21.6710817580159 | 27.79138064 | 135.276743 | 6 |
| part_00_density_Z_6_2 | 0.4772227986 | 10.7704268525 | 21.81239755 | 31.6558979266011 | 42.2018417175 | 263.894204 | 6 |
| part_00_density_Z_5_0 | 0.8740978443 | 5.13349933925 | 9.800981217 | 14.9658293492077 | 19.5972352825 | 118.2291655 | 6 |
| part_00_density_Z_5_1 | 2.141748592 | 8.24944651975 | 15.30460767 | 21.9599126016601 | 28.8064361275 | 167.0803952 | 6 |
| part_00_density_Z_4_2 | 0.5863015808 | 14.2823776825 | 23.620486935 | 32.412366435862 | 41.7400361 | 236.6704082 | 6 |
| part_00_density_Z_1_0 | 0.676804413 | 1.25011103 | 1.393010576 | 1.41602373112303 | 1.561421691 | 2.524396793 | 6 |
| part_00_density_Z_4_1 | 0.4739294732 | 12.58629058 | 21.055664985 | 28.6639689364339 | 37.27805028 | 204.5133587 | 6 |
| part_00_density_Z_7_2 | 2.886970336 | 9.3963800665 | 17.65901755 | 27.743643515339 | 36.2149550325 | 195.1189947 | 6 |
| part_00_density_Z_4_0 | 0.007392273944 | 7.077597242 | 12.82408083 | 17.0908168304135 | 23.095711625 | 122.5762619 | 6 |
| part_01_shape_segments_count | 0 | 3 | 15 | 284.837179491633 | 97 | 69202 | 0 |
| part_01_density_segments_count | 0 | 3 | 15 | 284.837179491633 | 97 | 69202 | 0 |
| part_01_volume | 0 | 4.224 | 10.392 | 25.4791179137298 | 26.016 | 1996.248 | 0 |
| part_01_electrons | 0 | 2.2866210385 | 6.190980086 | 15.16865422534 | 16.7891922825 | 395.6953318 | 0 |
| part_01_mean | 0 | 0.39721086955 | 0.56293219025 | 0.653247231679105 | 0.783701907775 | 8.85745132 | 0 |
| part_01_std | 0 | 0.052043102305 | 0.1081251083 | 0.198998555306524 | 0.2218051427 | 8.07543616 | 0 |
| part_01_max | 0 | 0.5643841177 | 0.8886601031 | 1.35122256735293 | 1.50641328075 | 44.63356781 | 0 |
| part_01_max_over_std | 0 | 5.23370470175 | 7.2410710645 | 9.73554817648152 | 11.2927055825 | 173.2519886 | 0 |
| part_01_skewness | 0 | 0.04384362348 | 0.09704538521 | 0.202875695940731 | 0.2187707617 | 10.7679468 | 13 |
| part_01_parts | 0 | 1 | 1 | 1.27001559769752 | 1 | 24 | 0 |
| part_01_shape_O3 | 74.84375 | 13104.27041 | 58573.090655 | 1280956.40279044 | 393236.8707 | 2085834000 | 5440 |
| part_01_shape_O4 | 1818.625 | 41149723.3525 | 848104045.5 | 5956168337577.82 | 31170402690 | 2.632981562e+17 | 5440 |
| part_01_shape_O5 | 13344.78125 | 35940501732.5 | 3376744517000 | 63339861689149931520 | 587440656125000 | 8.480461696e+24 | 5440 |
| part_01_shape_FL | 0 | 93945451.9675 | 10104271535 | 34778705113134480 | 2267288873750 | 5.267347841e+21 | 5440 |
| part_01_shape_O3_norm | 0.2273854245 | 0.2600788512 | 0.36671078095 | 0.534332827070869 | 0.67272941955 | 43.7516017 | 5440 |
| part_01_shape_O4_norm | 0.01700571523 | 0.02048194571 | 0.031168169965 | 0.0729633359021879 | 0.0796092871825 | 11.75142891 | 5440 |
| part_01_shape_O5_norm | 0.000369140625 | 0.00048549807635 | 0.00070076104105 | 0.00256256390575846 | 0.002034361633 | 1.2316115 | 5440 |
| part_01_shape_FL_norm | 0 | 0.000349437428875 | 0.004588516166 | 0.137173958791888 | 0.0460966194425 | 552.6108339 | 5440 |
| part_01_shape_I1 | 210.5035706 | 423040.731125 | 3833650.61 | 2246900615.73671 | 78884298.285 | 130739927100000 | 5440 |
| part_01_shape_I2 | 10919.68117 | 26727405527.5 | 2155846727500 | 1.5702881042089e+20 | 666205435900000 | 1.923967336e+25 | 5440 |
| part_01_shape_I3 | 9454.581688 | 63817191745 | 5864554284500 | 5.54912536338183e+22 | 3217882128250000 | 1.708172404e+28 | 5440 |
| part_01_shape_I4 | 0 | 46155538.7225 | 5637398279 | 19895143261396632 | 1443283869000 | 2.998392566e+21 | 5440 |
| part_01_shape_I5 | 0 | 5435983.01775 | 1530301829.5 | 9972768693315586 | 667725356950 | 1.485755716e+21 | 5440 |
| part_01_shape_I6 | 5359.461162 | 2458607312.25 | 101403559300 | 1047989679629554432 | 15993924435000 | 2.400810228e+23 | 5440 |
| part_01_shape_I1_norm | 0.06068494826 | 0.0883711269725 | 0.21468428545 | 0.753738079692252 | 0.7421346992 | 3426.135705 | 5440 |
| part_01_shape_I2_norm | 0.0009490396018 | 0.0016468309465 | 0.00563742424 | 0.231795333067002 | 0.04924281372 | 6729.605059 | 5440 |
| part_01_shape_I3_norm | 0.0007599305419 | 0.00232030185975 | 0.02213029832 | 53.5906224792912 | 0.317355875175 | 11734236.34 | 5440 |
| part_01_shape_I4_norm | 0 | 0.000156193069175 | 0.0026059228275 | 0.11126723606014 | 0.03005147577 | 605.613144 | 5440 |
| part_01_shape_I5_norm | 0 | 1.7624630785e-05 | 0.0008910358377 | 0.0939960875723411 | 0.0156107442275 | 640.9480174 | 5440 |
| part_01_shape_I6_norm | 0.004634817215 | 0.0089098663325 | 0.038712905335 | 1.43374817872382 | 0.276057532275 | 149861.8115 | 5440 |
| part_01_shape_M000 | 32 | 544 | 1318 | 3215.27063613696 | 3293 | 249531 | 5440 |
| part_01_shape_CI | -142.6431085 | -0.619050670475 | 0.00013464954605 | 0.0374705848761713 | 0.652208922275 | 91.32459492 | 5440 |
| part_01_shape_E3_E1 | 6.92565232e-05 | 0.0793733600775 | 0.1782402881 | 0.252419955385726 | 0.3893567043 | 0.9936373691 | 5440 |
| part_01_shape_E2_E1 | 8.955361535e-05 | 0.20649147405 | 0.39122195555 | 0.427362756062005 | 0.632565554825 | 1 | 5440 |
| part_01_shape_E3_E2 | 0.009098147053 | 0.379260800775 | 0.59205196085 | 0.56365845603382 | 0.7575550136 | 1 | 5440 |
| part_01_shape_sqrt_E1 | 0.9297130956 | 3.40275080725 | 5.240674933 | 7.47661828497442 | 9.536092817 | 202.3696755 | 5440 |
| part_01_shape_sqrt_E2 | 0.5280429429 | 2.20428105325 | 3.154479635 | 4.04488414606985 | 4.840142523 | 32.86795962 | 5440 |
| part_01_shape_sqrt_E3 | 0.3033367034 | 1.68098184325 | 2.3458148085 | 2.66849380271437 | 3.2275464365 | 19.36044844 | 5440 |
| part_01_density_O3 | 2.571448916 | 7042.63645575 | 32703.676825 | 676943.525020939 | 196094.5253 | 491201973.2 | 5440 |
| part_01_density_O4 | 2.110861979 | 11695940.37 | 258669321.9 | 1006066163187.54 | 7762409804.25 | 1.459114628e+16 | 5440 |
| part_01_density_O5 | 0.5480144926 | 5363095033.25 | 557452016550 | 1057047574391122304 | 73695870572500 | 1.102506511e+23 | 5440 |
| part_01_density_FL | -20.34378153 | 23064168.185 | 2763072341.5 | 2750050702399514 | 617112170350 | 2.970709623e+20 | 5440 |
| part_01_density_O3_norm | 0.03547024376 | 0.35534794635 | 0.5671874652 | 0.769401721971702 | 0.969884621025 | 309.7920829 | 5440 |
| part_01_density_O4_norm | 0.0004179190428 | 0.0361757793225 | 0.078083710485 | 0.155359766035792 | 0.1748354505 | 30.94691703 | 5440 |
| part_01_density_O5_norm | 1.636232857e-06 | 0.00105438747725 | 0.0027537674635 | 0.00837312346102849 | 0.00716141347575 | 24.61131367 | 5440 |
| part_01_density_FL_norm | -0.04060605278 | 0.0010451597725 | 0.01224254199 | 0.75219755625352 | 0.144025326775 | 11787.1847 | 5440 |
| part_01_density_I1 | 17.59328581 | 221357.268275 | 1981265.318 | 883211941.183915 | 38826488.985 | 10987932770000 | 5440 |
| part_01_density_I2 | 74.95620167 | 7249884357.75 | 583181098400 | 9748410448914219008 | 157319534375000 | 9.956763139e+23 | 5440 |
| part_01_density_I3 | 75.12815777 | 17313046457.5 | 1536264885000 | 7.37961232218467e+20 | 806747091375000 | 1.206633152e+26 | 5440 |
| part_01_density_I4 | -4.945613055 | 11665721.855 | 1644622303 | 1703744566900728 | 428330991500 | 1.786501129e+20 | 5440 |
| part_01_density_I5 | 0.0002380722297 | 2004751.65275 | 583917452.85 | 1006207142984878 | 233261454100 | 9.970287987e+19 | 5440 |
| part_01_density_I6 | 16.09444231 | 700412939.95 | 29048603100 | 30585859461919924 | 4004090003000 | 3.827443545e+21 | 5440 |
| part_01_density_I1_norm | 0.00173077621 | 0.180422890475 | 0.4966543015 | 2.65451867762104 | 1.59853848425 | 171129.3661 | 5440 |
| part_01_density_I2_norm | 7.899698444e-07 | 0.00625897574825 | 0.03428826519 | 2.13443586850323 | 0.238176799025 | 70258.06697 | 5440 |
| part_01_density_I3_norm | 6.126378935e-07 | 0.01027737212 | 0.10792886365 | 98737.9830596134 | 1.473325583 | 29268729010 | 5440 |
| part_01_density_I4_norm | -0.01530873544 | 0.000495792708625 | 0.007408200274 | 0.681920830166353 | 0.10028148265 | 12736.43029 | 5440 |
| part_01_density_I5_norm | 6.213496432e-11 | 7.2109551545e-05 | 0.0030848984955 | 0.63506967943117 | 0.060268517715 | 13369.26068 | 5440 |
| part_01_density_I6_norm | 2.062968655e-05 | 0.0256785699025 | 0.13133060095 | 217.594415290846 | 0.849932814775 | 52993730.2 | 5440 |
| part_01_density_M000 | 0.4672307847 | 295.748038225 | 786.94475115 | 1914.16864137956 | 2121.8320155 | 49461.91648 | 5440 |
| part_01_density_CI | -162.5799514 | -0.65561384585 | 9.958566425e-05 | 0.0374031569800578 | 0.6839140576 | 126.3449143 | 5440 |
| part_01_density_E3_E1 | 6.708289305e-05 | 0.076972645075 | 0.178817939 | 0.255153897264929 | 0.397125325975 | 0.9967620033 | 5440 |
| part_01_density_E2_E1 | 8.802525282e-05 | 0.202906345925 | 0.3924574027 | 0.427875865987626 | 0.63659338945 | 0.9999999635 | 5440 |
| part_01_density_E3_E2 | 0.00998371717 | 0.379942076475 | 0.5960110992 | 0.565813863360354 | 0.762010227975 | 0.9999999892 | 5440 |
| part_01_density_sqrt_E1 | 0.9251488726 | 3.2036552745 | 4.933182005 | 7.21091369046706 | 9.26569869675 | 202.1731968 | 5440 |
| part_01_density_sqrt_E2 | 0.5272160835 | 2.1123368925 | 2.959168708 | 3.86189808196988 | 4.59023102525 | 33.14079082 | 5440 |
| part_01_density_sqrt_E3 | 0.3032062157 | 1.6261534155 | 2.2231723435 | 2.53822473113101 | 3.02084362925 | 18.69134969 | 5440 |
| part_01_shape_Z_7_3 | 4.606066123 | 12.09751818 | 21.8113293 | 35.9600944315827 | 46.86009984 | 470.2779892 | 5440 |
| part_01_shape_Z_0_0 | 2.763953196 | 11.39607097 | 17.73835738 | 22.5366069222716 | 28.03829241 | 244.0719938 | 5440 |
| part_01_shape_Z_7_0 | 0.7064404485 | 6.62225404075 | 8.6565756005 | 16.0283496796321 | 19.801143925 | 291.5567921 | 5440 |
| part_01_shape_Z_7_1 | 3.417767679 | 8.49961757175 | 14.29260775 | 25.0581971238114 | 32.5698606975 | 370.9862843 | 5440 |
| part_01_shape_Z_3_0 | 0.6282218944 | 4.66837016525 | 8.9570880115 | 13.4663812225899 | 17.646771435 | 191.7557987 | 5440 |
| part_01_shape_Z_5_2 | 3.096687281 | 10.8147795875 | 20.40038273 | 30.3814917968245 | 39.650864895 | 403.2964918 | 5440 |
| part_01_shape_Z_6_1 | 0.7943246251 | 9.0767190005 | 16.849918395 | 27.450107206325 | 36.85894969 | 371.7026923 | 5440 |
| part_01_shape_Z_3_1 | 2.424590821 | 8.648598538 | 15.38328836 | 21.3691097003335 | 27.3341589375 | 260.6735527 | 5440 |
| part_01_shape_Z_6_0 | 0.008393562113 | 4.20443989375 | 8.14878628 | 13.1235461630222 | 17.03811458 | 263.6183335 | 5440 |
| part_01_shape_Z_2_1 | 1.712751415 | 15.1220757025 | 24.12450957 | 32.8034333369183 | 41.67242439 | 346.377309 | 5440 |
| part_01_shape_Z_6_3 | 3.40121215 | 14.0234116475 | 25.532903195 | 40.2983299960052 | 53.5072834225 | 537.1829066 | 5440 |
| part_01_shape_Z_2_0 | 0.05221444873 | 10.9115916 | 18.086630165 | 23.9048648241882 | 30.6459023075 | 289.365932 | 5440 |
| part_01_shape_Z_6_2 | 2.460815242 | 12.15297679 | 22.543723155 | 36.2135759018209 | 48.3792254175 | 494.9405429 | 5440 |
| part_01_shape_Z_5_0 | 0.7448828573 | 5.44049844825 | 9.6978304905 | 16.448963710732 | 21.801812285 | 295.2349679 | 5440 |
| part_01_shape_Z_5_1 | 2.413729259 | 8.26504698075 | 16.600978125 | 25.0506075062506 | 32.9170321375 | 368.1260643 | 5440 |
| part_01_shape_Z_4_2 | 2.219830577 | 14.27121821 | 25.54751238 | 37.4956528607191 | 49.319007305 | 450.5035985 | 5440 |
| part_01_shape_Z_1_0 | 0.7036783365 | 1.30235846875 | 1.495968985 | 1.54090076620245 | 1.72830205325 | 4.284077118 | 5440 |
| part_01_shape_Z_4_1 | 1.1381293 | 11.3807105875 | 21.641154295 | 32.0094977294515 | 42.6950088875 | 381.4826182 | 5440 |
| part_01_shape_Z_7_2 | 4.023330557 | 10.362821395 | 18.784816525 | 31.8740774920634 | 41.653699215 | 447.270409 | 5440 |
| part_01_shape_Z_4_0 | 8.736893748e-08 | 5.885822767 | 11.627850015 | 17.4499711542399 | 23.61082156 | 275.1723807 | 5440 |
| part_01_density_Z_7_3 | 2.597442104 | 9.3665346535 | 16.4906866 | 28.1533501479638 | 36.43670664 | 203.0543188 | 5440 |
| part_01_density_Z_0_0 | 0.3339807381 | 8.402656918 | 13.706539335 | 17.3622593167184 | 22.5066674675 | 108.6653705 | 5440 |
| part_01_density_Z_7_0 | 0.6196769627 | 6.264376259 | 7.769094827 | 14.3078697995574 | 17.5128330825 | 125.1703254 | 5440 |
| part_01_density_Z_7_1 | 1.905983822 | 7.4440417625 | 11.55521212 | 20.8819756674103 | 26.872968805 | 155.6780357 | 5440 |
| part_01_density_Z_3_0 | 0.4401991528 | 4.07715231175 | 6.870156347 | 10.7239338007393 | 13.75372718 | 86.31976138 | 5440 |
| part_01_density_Z_5_2 | 2.074456797 | 8.17127531425 | 15.31951505 | 23.5525607133642 | 30.8108761325 | 180.4895869 | 5440 |
| part_01_density_Z_6_1 | 0.1964239668 | 5.88752678525 | 13.86998076 | 22.2154184361373 | 30.9006994875 | 191.0917198 | 5440 |
| part_01_density_Z_3_1 | 1.000718192 | 6.360860014 | 11.14959335 | 16.1408737195999 | 20.7117984975 | 117.4498421 | 5440 |
| part_01_density_Z_6_0 | 0.007128359228 | 2.84757594925 | 6.210887308 | 11.3930304034275 | 15.7519760075 | 117.454081 | 5440 |
| part_01_density_Z_2_1 | 0.3559485489 | 11.72490052 | 19.13462546 | 25.4032831074403 | 32.26192846 | 170.921048 | 5440 |
| part_01_density_Z_6_3 | 0.3605836562 | 9.276769411 | 19.74930942 | 31.0712927723096 | 41.91014129 | 270.3135323 | 5440 |
| part_01_density_Z_2_0 | 0.05111619709 | 8.78888041725 | 14.88800351 | 19.3916757813683 | 25.6746105025 | 128.1324628 | 5440 |
| part_01_density_Z_6_2 | 0.2664103766 | 8.01580402375 | 17.93102783 | 28.3811904847144 | 38.6421786025 | 253.5044236 | 5440 |
| part_01_density_Z_5_0 | 0.6775005089 | 5.21914692525 | 8.223001392 | 14.0676536581323 | 18.18423288 | 114.6306509 | 5440 |
| part_01_density_Z_5_1 | 1.926643808 | 6.7983321145 | 12.87944272 | 20.0892589230736 | 26.4584280425 | 164.8664157 | 5440 |
| part_01_density_Z_4_2 | 0.2698715196 | 10.7368243675 | 20.312251725 | 29.0360454812364 | 38.3665900175 | 224.7521724 | 5440 |
| part_01_density_Z_1_0 | 0.6245716142 | 1.29014759525 | 1.48641199 | 1.5326320674948 | 1.72497565675 | 4.286519262 | 5440 |
| part_01_density_Z_4_1 | 0.1951852739 | 9.135848455 | 17.868556995 | 25.4206473096162 | 34.02279975 | 196.1613423 | 5440 |
| part_01_density_Z_7_2 | 2.255973215 | 8.45233439775 | 14.62473641 | 25.5420899899745 | 33.120387465 | 191.7016378 | 5440 |
| part_01_density_Z_4_0 | 0.005116128753 | 4.7206859845 | 10.52689981 | 15.0371050150514 | 20.9287306725 | 120.4580713 | 5440 |
| part_02_shape_segments_count | 0 | 2 | 9 | 238.344472891619 | 64 | 45564 | 0 |
| part_02_density_segments_count | 0 | 2 | 9 | 238.344472891619 | 64 | 45564 | 0 |
| part_02_volume | 0 | 2.352 | 7.416 | 19.6602305958043 | 19.624 | 1632.536 | 0 |
| part_02_electrons | 0 | 1.36412525925 | 4.798978621 | 12.956146413061 | 14.461346805 | 351.1866563 | 0 |
| part_02_mean | 0 | 0.40875314715 | 0.6024778514 | 0.679415222529393 | 0.845702438775 | 9.763456115 | 0 |
| part_02_std | 0 | 0.0392864827525 | 0.095020903225 | 0.187915748721414 | 0.2098935451 | 8.262893724 | 0 |
| part_02_max | 0 | 0.54700250925 | 0.8850423694 | 1.32471429847532 | 1.5056994855 | 44.63356781 | 0 |
| part_02_max_over_std | 0 | 5.23363722825 | 7.2410710645 | 9.50942215244704 | 11.2927055825 | 173.2519886 | 0 |
| part_02_skewness | 0 | 0.03185317297 | 0.08343037145 | 0.189945601707903 | 0.2035830531 | 10.89156506 | 25 |
| part_02_parts | 0 | 1 | 1 | 1.30159832976103 | 1 | 28 | 0 |
| part_02_shape_O3 | 74.3125 | 7761.589329 | 40927.09183 | 1021656.18329859 | 293778.0844 | 1668045255 | 39702 |
| part_02_shape_O4 | 1808.75 | 14227542.095 | 412575179.4 | 3620299822556.12 | 17002942115 | 1.649676022e+17 | 39702 |
| part_02_shape_O5 | 12288 | 7336670822.75 | 1138525507000 | 26554923938426335232 | 230587795050000 | 4.147785457e+24 | 39702 |
| part_02_shape_FL | -61.15935744 | 15757367.46 | 3460179126.5 | 20792723621479068 | 1283444917250 | 3.330358279e+21 | 39702 |
| part_02_shape_O3_norm | 0.2269145962 | 0.252823889925 | 0.33986987515 | 0.576596796112792 | 0.72544657455 | 68.88374187 | 39702 |
| part_02_shape_O4_norm | 0.01698600948 | 0.0197486930175 | 0.02779907854 | 0.088172510050944 | 0.089185339145 | 21.69250839 | 39702 |
| part_02_shape_O5_norm | 0.0003662109375 | 0.000473270513125 | 0.00062223259225 | 0.00352327566461323 | 0.00229637693 | 6.417807076 | 39702 |
| part_02_shape_FL_norm | -1.917847392e-05 | 0.000223390213975 | 0.003036618026 | 0.356666363091967 | 0.0604095641425 | 3374.84244 | 39702 |
| part_02_shape_I1 | 206.4160156 | 193009.61375 | 2281721.8465 | 1776270705.9079 | 56499196.58 | 105768622600000 | 39702 |
| part_02_shape_I2 | 10875.0353 | 5765009343 | 762232197450 | 9.210601238586e+19 | 316391191575000 | 1.085535104e+25 | 39702 |
| part_02_shape_I3 | 9186.614932 | 12341080600 | 1991182496000 | 3.61031737741658e+22 | 1716500067750000 | 1.118110825e+28 | 39702 |
| part_02_shape_I4 | -21.56396544 | 7399828.28725 | 1902936506.5 | 12219639147382290 | 848584396625 | 1.981338812e+21 | 39702 |
| part_02_shape_I5 | 0 | 681899.633075 | 413571480.05 | 6504249498206191 | 414028558800 | 1.081992501e+21 | 39702 |
| part_02_shape_I6 | 5232.473684 | 651649280.3 | 41526144795 | 680409428044665088 | 8660427188000 | 1.572613479e+23 | 39702 |
| part_02_shape_I1_norm | 0.06024977288 | 0.08167794873 | 0.1814324258 | 1.04345408200847 | 0.87937223295 | 8356.552153 | 39702 |
| part_02_shape_I2_norm | 0.0009412415709 | 0.00147633498625 | 0.0041767798395 | 0.821975350570804 | 0.064302032885 | 48073.17408 | 39702 |
| part_02_shape_I3_norm | 0.0007515553925 | 0.00185157000825 | 0.015568221055 | 180.072505992739 | 0.45494899035 | 69819220.74 | 39702 |
| part_02_shape_I4_norm | -6.478741585e-06 | 9.785099142e-05 | 0.0016810030595 | 0.320976282269867 | 0.0407703933125 | 3367.003644 | 39702 |
| part_02_shape_I5_norm | 0 | 8.92666823775e-06 | 0.00054023458345 | 0.297182895061494 | 0.02187051593 | 3361.77778 | 39702 |
| part_02_shape_I6_norm | 0.004609744519 | 0.007787616906 | 0.029931113065 | 3.02337420356417 | 0.35699184865 | 575558.1108 | 39702 |
| part_02_shape_M000 | 32 | 396 | 1055 | 2639.55203498351 | 2686 | 204067 | 39702 |
| part_02_shape_CI | -153.7476975 | -0.465816351425 | 8.7582609795e-05 | 0.0312865058382261 | 0.49248775785 | 147.0380863 | 39702 |
| part_02_shape_E3_E1 | 3.085697577e-05 | 0.075523331035 | 0.19697029115 | 0.267573838733583 | 0.427421510775 | 0.9950984259 | 39702 |
| part_02_shape_E2_E1 | 4.942462443e-05 | 0.2054791524 | 0.41344631305 | 0.438497128602378 | 0.6567165697 | 1 | 39702 |
| part_02_shape_E3_E2 | 0.01024688429 | 0.390777349725 | 0.6141010651 | 0.575245300462736 | 0.77307132295 | 1 | 39702 |
| part_02_shape_sqrt_E1 | 0.9435479746 | 2.96577894975 | 4.699304913 | 7.13045757555409 | 9.3247117125 | 201.8139635 | 39702 |
| part_02_shape_sqrt_E2 | 0.5644686158 | 1.96504764575 | 2.916646107 | 3.80738923210685 | 4.580073386 | 33.30702555 | 39702 |
| part_02_shape_sqrt_E3 | 0.4024232911 | 1.5222660025 | 2.198126123 | 2.50235316521196 | 3.063427251 | 18.5431693 | 39702 |
| part_02_density_O3 | 9.46406785 | 4555.53294975 | 25477.65995 | 594880.09378333 | 164893.795675 | 422873659.4 | 39702 |
| part_02_density_O4 | 26.47290094 | 4808538.35325 | 154607381.45 | 768277832931.513 | 5406225111 | 1.060964832e+16 | 39702 |
| part_02_density_O5 | 19.57740725 | 1413065261.75 | 256873803000 | 675171599751762816 | 42366473562500 | 6.745875771e+22 | 39702 |
| part_02_density_FL | -23.32580548 | 5078585.41125 | 1157646567.5 | 2099456805735417 | 446837849375 | 2.126358836e+20 | 39702 |
| part_02_density_O3_norm | 0.03293952489 | 0.320998654975 | 0.51047334995 | 0.777368432201909 | 0.965283057125 | 382.9768645 | 39702 |
| part_02_density_O4_norm | 0.0003613885822 | 0.0301383967075 | 0.06558358168 | 0.163864560494721 | 0.1669607447 | 115.5475918 | 39702 |
| part_02_density_O5_norm | 1.320574892e-06 | 0.00083098379735 | 0.002213842025 | 0.00935395532604198 | 0.006431268816 | 113.0485047 | 39702 |
| part_02_density_FL_norm | -0.004686326327 | 0.0005567944075 | 0.0066044615425 | 2.32177617891657 | 0.1493438097 | 197912.7855 | 39702 |
| part_02_density_I1 | 26.90263097 | 111870.2857 | 1350646.141 | 770781966.076257 | 31631680.045 | 9365255920000 | 39702 |
| part_02_density_I2 | 179.7692352 | 1934168153.5 | 265382501550 | 7221280880166855680 | 97081626895000 | 6.907748438e+23 | 39702 |
| part_02_density_I3 | 162.2540673 | 4171797142.5 | 674704013750 | 5.5292879315094e+20 | 554792820050000 | 8.766542159e+25 | 39702 |
| part_02_density_I4 | -5.770646085 | 2443559.02875 | 666766726.3 | 1342962137663308 | 319285565900 | 1.31442451e+20 | 39702 |
| part_02_density_I5 | 0.0002899668474 | 343057.974875 | 190859719.85 | 838632358922868 | 178789474625 | 7.731349589e+19 | 39702 |
| part_02_density_I6 | 88.32222845 | 226539462.85 | 15542664580 | 23518571592212004 | 2767427247000 | 2.750679082e+21 | 39702 |
| part_02_density_I1_norm | 0.001492929285 | 0.1432702702 | 0.3926676432 | 3.00463023855793 | 1.61836514375 | 258303.8672 | 39702 |
| part_02_density_I2_norm | 5.929662497e-07 | 0.00411563307825 | 0.022854090795 | 11.5034934619185 | 0.227504833525 | 2154055.586 | 39702 |
| part_02_density_I3_norm | 4.480855128e-07 | 0.006156361564 | 0.063868690145 | 149071.179621009 | 1.54129865525 | 66708791400 | 39702 |
| part_02_density_I4_norm | -0.001808171149 | 0.0002545523456 | 0.0038807222625 | 2.38647363837757 | 0.10799313355 | 264833.3131 | 39702 |
| part_02_density_I5_norm | 1.157187674e-10 | 2.895409806e-05 | 0.0015236418635 | 2.42960527805216 | 0.0665502713075 | 309446.9982 | 39702 |
| part_02_density_I6_norm | 1.642012403e-05 | 0.0180519646 | 0.09089457529 | 254.496948974585 | 0.8676927075 | 98912031.52 | 39702 |
| part_02_density_M000 | 2.538354646 | 234.029745475 | 692.44037595 | 1739.47210148389 | 1966.34057925 | 43898.33204 | 39702 |
| part_02_density_CI | -166.928922 | -0.488644906875 | 6.4344343615e-05 | 0.0297757557168502 | 0.510791552175 | 167.5373289 | 39702 |
| part_02_density_E3_E1 | 3.077645341e-05 | 0.0738855604825 | 0.1995912299 | 0.270382630574708 | 0.434014719525 | 0.9964265156 | 39702 |
| part_02_density_E2_E1 | 4.898493277e-05 | 0.202735579175 | 0.41535099 | 0.439309947009086 | 0.660192483975 | 0.9999999682 | 39702 |
| part_02_density_E3_E2 | 0.009932988958 | 0.392107933975 | 0.61837762295 | 0.577576713405616 | 0.7772478897 | 0.9999999766 | 39702 |
| part_02_density_sqrt_E1 | 0.9318626049 | 2.8179456865 | 4.4102065865 | 6.89287411221691 | 9.07444980675 | 201.7050834 | 39702 |
| part_02_density_sqrt_E2 | 0.5635506026 | 1.8984330805 | 2.7472572575 | 3.64770540560666 | 4.351791953 | 32.35449294 | 39702 |
| part_02_density_sqrt_E3 | 0.4014297725 | 1.4820386485 | 2.093738484 | 2.39116401624088 | 2.8762564935 | 17.84455462 | 39702 |
| part_02_shape_Z_7_3 | 5.83960079 | 10.95182318 | 18.58391625 | 32.7766026873652 | 42.7081337025 | 416.5654831 | 39702 |
| part_02_shape_Z_0_0 | 2.763953196 | 9.723067222 | 15.87018265 | 20.147430614394 | 25.32262359 | 220.7202022 | 39702 |
| part_02_shape_Z_7_0 | 0.9095853601 | 6.78265832475 | 8.474385616 | 15.2669465899787 | 18.23870205 | 228.8372883 | 39702 |
| part_02_shape_Z_7_1 | 3.760529496 | 8.452370902 | 12.23535068 | 23.1681397127822 | 29.80664404 | 319.7387226 | 39702 |
| part_02_shape_Z_3_0 | 0.4922365492 | 4.4493366335 | 7.6246062965 | 12.4464497816764 | 16.344487415 | 195.1590497 | 39702 |
| part_02_shape_Z_5_2 | 3.978093159 | 9.084246169 | 17.43752889 | 27.4420867306156 | 35.9858526475 | 344.7866219 | 39702 |
| part_02_shape_Z_6_1 | 0.971167048 | 7.2828897715 | 14.290491325 | 24.5333529910363 | 33.0763657675 | 340.5182007 | 39702 |
| part_02_shape_Z_3_1 | 2.615481061 | 7.162718439 | 13.53123637 | 19.3983181791035 | 24.9850614725 | 261.961261 | 39702 |
| part_02_shape_Z_6_0 | 0.002431445993 | 3.44720971775 | 6.995242045 | 11.9289881262018 | 15.3220231875 | 204.6875772 | 39702 |
| part_02_shape_Z_2_1 | 1.587596451 | 12.58147584 | 21.060789165 | 29.1206179674716 | 37.3633818875 | 315.9119291 | 39702 |
| part_02_shape_Z_6_3 | 3.177852956 | 11.16967189 | 21.823906075 | 36.0692148597777 | 48.48289561 | 495.4178011 | 39702 |
| part_02_shape_Z_2_0 | 0.05221444873 | 8.8764735855 | 15.58819009 | 21.0831377924912 | 27.313042865 | 264.7737438 | 39702 |
| part_02_shape_Z_6_2 | 2.169626771 | 9.60316095675 | 19.086345765 | 32.2652896361917 | 43.5397600275 | 461.0860046 | 39702 |
| part_02_shape_Z_5_0 | 0.7615551244 | 5.5291010585 | 7.9410453025 | 15.315489520728 | 20.0348455575 | 241.832509 | 39702 |
| part_02_shape_Z_5_1 | 2.705489715 | 7.41826726525 | 13.95902084 | 22.6272674895301 | 29.7633400925 | 300.3947766 | 39702 |
| part_02_shape_Z_4_2 | 2.174361229 | 11.415190415 | 21.63106506 | 33.2315383129167 | 44.39495124 | 412.1893426 | 39702 |
| part_02_shape_Z_1_0 | 0.6729881274 | 1.33626038675 | 1.5875655115 | 1.65203204494229 | 1.8719790345 | 5.053228749 | 39702 |
| part_02_shape_Z_4_1 | 0.8847612903 | 9.0189049465 | 18.005069035 | 28.1730608540004 | 38.10938988 | 355.2037823 | 39702 |
| part_02_shape_Z_7_2 | 4.534117032 | 9.758163834 | 15.86383032 | 29.0252741518712 | 37.728873865 | 382.3021123 | 39702 |
| part_02_shape_Z_4_0 | 0.009469098667 | 4.64735286925 | 9.534040697 | 15.4366974336642 | 20.920627515 | 247.7431767 | 39702 |
| part_02_density_Z_7_3 | 3.205354241 | 9.372090008 | 14.5484575 | 26.9787046973951 | 34.8969087975 | 200.1822739 | 39702 |
| part_02_density_Z_0_0 | 0.7784520113 | 7.47465626175 | 12.85721443 | 16.3660078715098 | 21.6663156675 | 102.3716504 | 39702 |
| part_02_density_Z_7_0 | 0.952241736 | 6.51356552875 | 8.066543796 | 14.1530749066335 | 16.767902805 | 122.9814966 | 39702 |
| part_02_density_Z_7_1 | 1.985287665 | 7.688617466 | 10.357224035 | 20.184689267479 | 25.6340453675 | 151.618603 | 39702 |
| part_02_density_Z_3_0 | 0.5339320117 | 4.14633999325 | 6.2251214255 | 10.4396666470794 | 13.3790933725 | 83.37841647 | 39702 |
| part_02_density_Z_5_2 | 2.333199775 | 7.7132597825 | 13.68352834 | 22.4233201636486 | 29.5256174625 | 178.4799195 | 39702 |
| part_02_density_Z_6_1 | 0.4645438648 | 5.08653844275 | 11.412295125 | 20.6536988439468 | 29.26476223 | 185.8141834 | 39702 |
| part_02_density_Z_3_1 | 1.9646589 | 5.83998322925 | 10.31664064 | 15.4909861945341 | 20.03386739 | 113.8338572 | 39702 |
| part_02_density_Z_6_0 | 0.0005344082229 | 2.44753902225 | 5.201348063 | 10.7199911148064 | 14.706057065 | 115.1505833 | 39702 |
| part_02_density_Z_2_1 | 0.7793738898 | 10.23846919 | 17.66268559 | 23.7705085344482 | 30.72985265 | 165.2802441 | 39702 |
| part_02_density_Z_6_3 | 0.9761576627 | 7.8368919375 | 17.064881265 | 29.0878916812011 | 40.09359629 | 257.0873277 | 39702 |
| part_02_density_Z_2_0 | 0.02936858271 | 7.50111499175 | 13.563926415 | 18.0357062103476 | 24.3790405625 | 120.5566076 | 39702 |
| part_02_density_Z_6_2 | 0.7662380856 | 6.6980886665 | 15.24479204 | 26.4059686276437 | 36.68089811 | 242.5491618 | 39702 |
| part_02_density_Z_5_0 | 0.6352722861 | 5.37321612575 | 7.455046631 | 13.6707422595879 | 17.447302955 | 111.3185305 | 39702 |
| part_02_density_Z_5_1 | 1.68343546 | 6.70053440925 | 11.31865804 | 19.0947615319076 | 25.1615600125 | 162.4163936 | 39702 |
| part_02_density_Z_4_2 | 0.7775913047 | 8.53880109975 | 18.077851205 | 26.9512001448052 | 36.554214565 | 214.2124261 | 39702 |
| part_02_density_Z_1_0 | 0.6087433634 | 1.32398143025 | 1.5804985995 | 1.64451789979272 | 1.8694510785 | 5.050802593 | 39702 |
| part_02_density_Z_4_1 | 0.3994020304 | 6.92388709025 | 15.6675129 | 23.3898528814388 | 32.113628065 | 187.5631296 | 39702 |
| part_02_density_Z_7_2 | 2.609323469 | 8.5956354925 | 12.778000365 | 24.4172710099089 | 31.4669965975 | 188.3994704 | 39702 |
| part_02_density_Z_4_0 | 0.005330786982 | 3.361982422 | 8.923390504 | 13.7930174215912 | 19.5086235125 | 119.3436982 | 39702 |
| fo_col | 575726 | character | character | 575726 | character | character | 575726 |
| fc_col | 575726 | character | character | 575726 | character | character | 575726 |
| weight_col | logical | 575726 | logical | 575726 | logical | 575726 | logical |
| grid_space | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 |
| solvent_radius | 1.9 | 1.9 | 1.9 | 1.9 | 1.9 | 1.9 | 1.9 |
| solvent_opening_radius | 1.4 | 1.4 | 1.4 | 1.4 | 1.4 | 1.4 | 1.4 |
| resolution_max_limit | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| resolution | 0.4800812304 | 1.79998827 | 2.076049328 | 2.15048560488871 | 2.482087612 | 8.999694824 | 0.4800812304 |
| FoFc_mean | -1.942057963e-07 | -4.618861196e-11 | 7.822532769e-13 | 4.25100650827451e-11 | 4.964862549e-11 | 3.621388771e-07 | -1.942057963e-07 |
| FoFc_std | 0.001250090112 | 0.09013658464 | 0.1223734106 | 0.128956289622333 | 0.1591430283 | 0.9418859565 | 0.001250090112 |
| FoFc_square_std | 1.562725288e-06 | 0.00812460389 | 0.01497525163 | 0.0195485813333313 | 0.02532650344 | 0.8871491551 | 1.562725288e-06 |
| FoFc_min | -10.821105 | -0.848829031 | -0.6640108824 | -0.700363778077503 | -0.499686718 | -0.01075177453 | -10.821105 |
| FoFc_max | 0.007184891496 | 1.141174555 | 1.847463131 | 2.60529588208993 | 3.082387924 | 45.26153183 | 0.007184891496 |
| part_step_FoFc_std_min | 2.8 | 2.8 | 2.8 | 2.8 | 2.8 | 2.8 | 2.8 |
| part_step_FoFc_std_max | 4.05 | 4.05 | 4.05 | 4.05 | 4.05 | 4.05 | 4.05 |
| part_step_FoFc_std_step | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
Kod ograniczający liczbę klas (res_name) do 50 najpopularniejszych wartości.
most_popular <- all_summary %>% group_by(res_name) %>% summarise(count=n()) %>% arrange(desc(count)) %>% head(50)
all_summary %<>% filter(res_name %in% most_popular$res_name)
Sekcja sprawdzająca korelacje między zmiennymi; sekcja ta powinna zawierać jakąś formę graficznej prezentacji korelacji.
ggplot(all_summary, aes(x=local_res_atom_non_h_count, y=dict_atom_non_h_count)) + geom_point() + ggtitle("local_res_atom_non_h_count vs dict_atom_non_h_count") + geom_smooth(method=lm, se=FALSE) + scale_x_continuous(name = "local_res_atom_non_h_count") + scale_y_continuous(name = "dict_atom_non_h_count") + theme(plot.title = element_text(hjust = 0.5), panel.background = element_blank(), axis.line = element_line(color="black"), axis.line.x = element_line(color="black")) + theme_bw()
ggplot(all_summary, aes(x=local_res_atom_non_h_electron_sum, y=dict_atom_non_h_electron_sum )) + geom_point() + ggtitle("local_res_atom_non_h_electron_sum vs dict_atom_non_h_electron_sum ") + geom_smooth(method=lm, se=FALSE) + scale_x_continuous(name = "local_res_atom_non_h_electron_sum") + scale_y_continuous(name = "dict_atom_non_h_electron_sum ") + theme(plot.title = element_text(hjust = 0.5), panel.background = element_blank(), axis.line = element_line(color="black"), axis.line.x = element_line(color="black")) + theme_bw()
ggplot(all_summary, aes(x=local_res_atom_C_count, y=dict_atom_C_count )) + geom_point() + ggtitle("local_res_atom_C_count vs dict_atom_C_count ") + geom_smooth(method=lm, se=FALSE) + scale_x_continuous(name = "local_res_atom_C_count") + scale_y_continuous(name = "dict_atom_C_count ") + theme(plot.title = element_text(hjust = 0.5), panel.background = element_blank(), axis.line = element_line(color="black"), axis.line.x = element_line(color="black")) + theme_bw()
ggplot(all_summary, aes(x=local_res_atom_N_count, y=dict_atom_N_count )) + geom_point() + ggtitle("local_res_atom_N_count vs dict_atom_N_count ") + geom_smooth(method=lm, se=FALSE) + scale_x_continuous(name = "local_res_atom_N_count") + scale_y_continuous(name = "dict_atom_N_count ") + theme(plot.title = element_text(hjust = 0.5), panel.background = element_blank(), axis.line = element_line(color="black"), axis.line.x = element_line(color="black")) + theme_bw()
ggplot(all_summary, aes(x=local_res_atom_O_count, y=dict_atom_O_count)) + geom_point() + ggtitle("local_res_atom_O_count vs dict_atom_O_count") + geom_smooth(method=lm, se=FALSE) + scale_x_continuous(name = "local_res_atom_O_count") + scale_y_continuous(name = "dict_atom_O_count") + theme(plot.title = element_text(hjust = 0.5), panel.background = element_blank(), axis.line = element_line(color="black"), axis.line.x = element_line(color="black")) + theme_bw()
ggplot(all_summary, aes(x=local_res_atom_S_count, y=dict_atom_S_count)) + geom_point() + ggtitle("local_res_atom_S_count vs dict_atom_S_count") + geom_smooth(method=lm, se=FALSE) + scale_x_continuous(name = "local_res_atom_S_count") + scale_y_continuous(name = "dict_atom_S_count") + theme(plot.title = element_text(hjust = 0.5), panel.background = element_blank(), axis.line = element_line(color="black"), axis.line.x = element_line(color="black")) + theme_bw()
Określenie ile przykładów ma każda z klas (res_name).
kable(most_popular %>% select(res_name, count)) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = FALSE)
| res_name | count |
|---|---|
| SO4 | 56572 |
| GOL | 40606 |
| EDO | 30825 |
| NAG | 26360 |
| CL | 23223 |
| CA | 21038 |
| ZN | 19826 |
| MG | 14779 |
| HEM | 11192 |
| PO4 | 11090 |
| ACT | 8096 |
| DMS | 6633 |
| IOD | 6317 |
| PEG | 4987 |
| CLA | 4784 |
| K | 4706 |
| FAD | 4555 |
| NAD | 4501 |
| MN | 4215 |
| ADP | 3819 |
| MLY | 3509 |
| NAP | 3505 |
| CD | 3242 |
| MPD | 3221 |
| FMT | 2918 |
| MAN | 2841 |
| PG4 | 2768 |
| MES | 2697 |
| CU | 2353 |
| ATP | 2296 |
| COA | 2183 |
| 1PE | 2136 |
| BR | 2127 |
| NDP | 2106 |
| FMN | 2084 |
| EPE | 1933 |
| HEC | 1917 |
| PGE | 1905 |
| TRS | 1656 |
| SF4 | 1647 |
| NI | 1637 |
| ACY | 1609 |
| FE | 1602 |
| NO3 | 1596 |
| PLP | 1594 |
| GDP | 1589 |
| SAH | 1587 |
| FE2 | 1560 |
| SEP | 1491 |
| CIT | 1464 |
Wykresy rozkładów liczby atomów (local_res_atom_non_h_count) i elektronów (local_res_atom_non_h_electron_sum).
ggplotly(ggplot(data=all_summary, aes(all_summary$local_res_atom_non_h_count)) + geom_histogram(binwidth = 1, col = "black", fill="blue", alpha = .2) + ggtitle("Rozkład liczby atomów") + scale_x_continuous("Liczba atomów"))
ggplotly(ggplot(data=all_summary, aes(all_summary$local_res_atom_non_h_electron_sum)) + geom_histogram(binwidth = 1, col = "black", fill="blue", alpha = .2) + ggtitle("Rozkład liczby elektronów") + scale_x_continuous("Liczba elektronów"))
Tabela pokazująca 10 klas z największą niezgodnością liczby atomów (local_res_atom_non_h_count vs dict_atom_non_h_count) i tabelę pokazującą 10 klas z największą niezgodnością liczby elektronów (local_res_atom_non_h_electron_sum vs dict_atom_non_h_electron_sum;)
kable(all_summary %>% filter(!is.na(res_name)) %>% group_by(res_name) %>% summarise(mean_incompatibility = mean(abs(local_res_atom_non_h_count - dict_atom_non_h_count), na.rm = TRUE)) %>% arrange(desc(mean_incompatibility)) %>% head(10)) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = FALSE)
| res_name | mean_incompatibility |
|---|---|
| CLA | 5.2451923 |
| 1PE | 2.6633895 |
| COA | 1.8346312 |
| MLY | 1.3265888 |
| NAP | 1.2833096 |
| PG4 | 1.0440751 |
| SEP | 1.0087190 |
| NDP | 0.9881292 |
| NAG | 0.9801214 |
| MAN | 0.8944034 |
kable(all_summary %>% filter(!is.na(res_name)) %>% group_by(res_name) %>% summarise(mean_incompatibility = mean(abs(local_res_atom_non_h_electron_sum - dict_atom_non_h_electron_sum), na.rm = TRUE)) %>% arrange(desc(mean_incompatibility)) %>% head(10)) %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = FALSE)
| res_name | mean_incompatibility |
|---|---|
| CLA | 31.846990 |
| 1PE | 18.161985 |
| COA | 13.783326 |
| MLY | 9.976062 |
| NAP | 8.630242 |
| SEP | 8.126090 |
| NAG | 7.838695 |
| MAN | 7.155227 |
| PG4 | 7.059971 |
| PLP | 6.874530 |
Sekcja pokazująca rozkład wartości wszystkich kolumn zaczynających się od part_01 z zaznaczeniem (graficznym i liczbowym) średniej wartości.
for (name in names(all_summary %>% select(starts_with("part_01"))) %>% tail(1)) {
print(ggplot(data=all_summary, aes(all_summary[[name]])) + geom_histogram(binwidth = 1, col = "black", fill="blue", alpha = .2) + geom_vline(aes(xintercept = mean(all_summary[[name]], na.rm = T)), color="red", linetype="dotted", size=1) + scale_x_continuous(name = name,breaks = mean(all_summary[[name]], na.rm = T)))
}
Interaktywne wykresy stworzono dla rozkładów wartości atomów i elektronów.
Sekcja sprawdzająca czy na podstawie wartości innych kolumn można przewidzieć liczbę elektronów i atomów oraz z jaką dokładnością można dokonać takiej predykcji; trafność regresji powinna zostać oszacowana na podstawie miar R^2 i RMSE;
gy <- c("local_volume", "local_electrons", "local_mean", "local_std", "local_min", "local_max", "local_skewness", "resolution")
all_summary %<>% head(50000)
all_summary_atoms <- all_summary %>% select(starts_with("part_0"), local_res_atom_non_h_count, starts_with("FoFc_"), gy) %>% na.omit()
idx <- createDataPartition(all_summary_atoms$local_res_atom_non_h_count, p=0.7, list=FALSE)
trainingData <- data.frame(all_summary_atoms[idx,])
testData <- data.frame(all_summary_atoms[-idx,])
ctrl <- trainControl(
# powtórzona ocena krzyżowa
method = "repeatedcv",
# liczba podziałów
number = 2,
# liczba powtórzeń
repeats = 5)
train(local_res_atom_non_h_count ~ .,
data = trainingData,
method = "lm",
trControl = ctrl)
## Linear Regression
##
## 32867 samples
## 331 predictor
##
## No pre-processing
## Resampling: Cross-Validated (2 fold, repeated 5 times)
## Summary of sample sizes: 16434, 16433, 16434, 16433, 16433, 16434, ...
## Resampling results:
##
## RMSE Rsquared MAE
## 47.03144 0.2036114 5.225487
##
## Tuning parameter 'intercept' was held constant at a value of TRUE
all_summary_electrons <- all_summary %>% select(starts_with("part_0"), local_res_atom_non_h_electron_sum, starts_with("FoFc_"), gy) %>% na.omit()
idx <- createDataPartition(all_summary_electrons$local_res_atom_non_h_electron_sum, p=0.7, list=FALSE)
trainingData <- data.frame(all_summary_electrons[idx,])
testData <- data.frame(all_summary_electrons[-idx,])
ctrl <- trainControl(
# powtórzona ocena krzyżowa
method = "repeatedcv",
# liczba podziałów
number = 2,
# liczba powtórzeń
repeats = 5)
train(local_res_atom_non_h_electron_sum ~ .,
data = trainingData,
method = "lm",
trControl = ctrl)
## Linear Regression
##
## 32868 samples
## 331 predictor
##
## No pre-processing
## Resampling: Cross-Validated (2 fold, repeated 5 times)
## Summary of sample sizes: 16433, 16435, 16433, 16435, 16433, 16435, ...
## Resampling results:
##
## RMSE Rsquared MAE
## 114.627 0.2928972 33.59331
##
## Tuning parameter 'intercept' was held constant at a value of TRUE
Sekcja próbująca stworzyć klasyfikator przewidujący wartość atrybutu res_name (w tej sekcji należy wykorzystać wiedzę z pozostałych punktów oraz wykonać dodatkowe czynności, które mogą poprawić trafność klasyfikacji); trafność klasyfikacji powinna zostać oszacowana na danych inne niż uczące za pomocą mechanizmu (stratyfikowanej!) oceny krzyżowej lub (stratyfikowanego!) zbioru testowego.
all_summary %<>% select(starts_with("part_0"), res_name, starts_with("FoFc_"), gy) %>% na.omit()
inTraining <-
createDataPartition(
# atrybut do stratyfikacji
y = all_summary$res_name,
# procent w zbiorze uczącym
p = .75,
# chcemy indeksy a nie listę
list = FALSE)
training <- all_summary[ inTraining,]
testing <- all_summary[-inTraining,]
ctrl <- trainControl(
# powtórzona ocena krzyżowa
method = "repeatedcv",
# liczba podziałów
number = 2,
# liczba powtórzeń
repeats = 5)
fit <- train(res_name ~ .,
data = training,
method = "rf",
trControl = ctrl,
ntree = 10)
fit
## Random Forest
##
## 35232 samples
## 331 predictor
## 50 classes: '1PE', 'ACT', 'ACY', 'ADP', 'ATP', 'BR', 'CA', 'CD', 'CIT', 'CL', 'CLA', 'COA', 'CU', 'DMS', 'EDO', 'EPE', 'FAD', 'FE', 'FE2', 'FMN', 'FMT', 'GDP', 'GOL', 'HEC', 'HEM', 'IOD', 'K', 'MAN', 'MES', 'MG', 'MLY', 'MN', 'MPD', 'NAD', 'NAG', 'NAP', 'NDP', 'NI', 'NO3', 'PEG', 'PG4', 'PGE', 'PLP', 'PO4', 'SAH', 'SEP', 'SF4', 'SO4', 'TRS', 'ZN'
##
## No pre-processing
## Resampling: Cross-Validated (2 fold, repeated 5 times)
## Summary of sample sizes: 17617, 17615, 17617, 17615, 17614, 17618, ...
## Resampling results across tuning parameters:
##
## mtry Accuracy Kappa
## 2 0.3831461 0.3273827
## 166 0.4189545 0.3673255
## 331 0.4185630 0.3671520
##
## Accuracy was used to select the optimal model using the largest value.
## The final value used for the model was mtry = 166.
rf_res_names <- predict(fit, newdata = testing)
confusionMatrix(table(data = rf_res_names, testing$res_name))
## Confusion Matrix and Statistics
##
##
## data 1PE ACT ACY ADP ATP BR CA CD CIT CL CLA COA CU
## 1PE 11 0 1 0 0 0 0 0 1 0 0 0 0
## ACT 1 28 5 0 0 1 5 3 1 6 0 0 1
## ACY 0 0 2 0 0 0 0 0 1 3 0 0 0
## ADP 0 0 0 31 10 0 1 0 0 0 0 0 0
## ATP 0 0 0 8 21 0 0 1 1 0 0 0 0
## BR 0 0 0 0 0 11 0 0 0 6 0 0 0
## CA 1 3 2 0 0 7 328 11 0 40 0 2 11
## CD 0 0 0 0 0 3 1 23 0 1 0 0 2
## CIT 0 0 0 1 1 0 0 0 5 0 0 0 0
## CL 3 13 7 2 0 21 67 6 2 424 0 4 3
## CLA 0 0 0 0 0 0 0 0 0 0 21 0 0
## COA 0 0 0 0 1 0 0 0 0 0 0 3 0
## CU 0 1 0 0 0 0 3 2 0 2 0 0 10
## DMS 0 7 0 0 0 1 5 0 0 9 0 1 0
## EDO 19 52 11 2 3 9 23 1 3 51 0 9 0
## EPE 1 1 0 0 0 0 1 0 0 1 0 0 0
## FAD 0 0 0 4 2 0 0 0 0 0 0 1 0
## FE 0 0 0 0 0 0 0 2 0 3 0 0 0
## FE2 0 0 0 0 0 0 0 0 0 0 0 0 0
## FMN 0 0 0 2 0 0 0 0 0 1 0 0 0
## FMT 0 4 0 0 0 0 0 0 0 0 0 0 0
## GDP 0 1 0 6 2 0 0 0 0 0 0 0 0
## GOL 23 41 12 5 4 4 38 3 15 57 0 7 0
## HEC 0 0 0 0 0 0 0 0 0 0 0 0 0
## HEM 0 5 0 3 0 0 0 0 1 2 1 1 1
## IOD 0 0 1 0 0 7 7 7 0 5 0 0 3
## K 0 1 0 0 0 1 5 1 0 7 0 0 0
## MAN 1 1 1 0 0 0 1 0 0 0 1 3 0
## MES 1 0 0 0 0 0 1 0 0 1 0 0 0
## MG 0 1 2 1 0 0 30 2 0 15 0 0 3
## MLY 0 1 0 0 0 0 1 0 0 1 0 0 0
## MN 0 2 1 0 0 0 7 3 0 0 0 1 0
## MPD 0 1 0 0 0 0 1 0 1 0 0 0 0
## NAD 0 0 0 3 3 0 1 0 0 1 0 2 0
## NAG 8 7 2 15 12 1 15 0 9 11 6 14 0
## NAP 0 0 0 1 0 0 0 0 0 0 0 1 0
## NDP 0 0 0 1 1 0 0 0 0 0 0 1 0
## NI 0 0 0 0 0 0 1 0 0 0 0 0 0
## NO3 0 0 0 0 0 0 0 0 0 1 0 0 0
## PEG 0 0 1 0 0 0 0 0 1 4 0 2 0
## PG4 0 0 0 0 0 0 0 0 2 1 0 0 0
## PGE 0 0 0 0 0 0 0 0 0 1 0 0 0
## PLP 0 0 0 0 0 0 1 0 0 0 0 1 0
## PO4 0 4 0 0 0 1 4 0 2 5 0 0 0
## SAH 0 0 0 5 4 0 1 0 0 0 0 1 0
## SEP 0 0 0 2 2 0 1 0 0 0 0 0 0
## SF4 0 1 0 2 0 0 0 0 0 0 0 0 0
## SO4 4 37 25 7 4 15 109 12 5 126 1 15 10
## TRS 0 0 0 1 0 0 0 0 0 0 0 0 0
## ZN 0 9 1 0 0 2 35 24 3 8 0 1 29
##
## data DMS EDO EPE FAD FE FE2 FMN FMT GDP GOL HEC HEM IOD
## 1PE 1 0 0 0 0 0 0 1 1 4 0 2 0
## ACT 2 9 1 1 0 1 0 1 0 15 0 3 3
## ACY 1 1 0 0 0 0 0 1 0 1 0 1 0
## ADP 0 0 0 0 0 0 2 0 11 3 0 0 0
## ATP 0 1 0 0 0 0 0 0 1 2 0 0 0
## BR 1 0 0 0 0 0 0 1 0 0 0 0 2
## CA 3 7 4 0 3 6 2 0 0 12 1 6 19
## CD 0 0 0 0 1 0 0 0 1 1 0 0 6
## CIT 0 0 0 0 0 0 0 0 0 1 0 0 0
## CL 14 44 3 3 1 1 0 6 1 46 1 4 29
## CLA 0 0 0 0 0 0 0 0 0 1 0 0 0
## COA 1 0 0 0 0 0 1 0 0 0 0 1 1
## CU 0 0 0 0 0 0 0 0 0 0 0 1 2
## DMS 89 12 0 0 0 0 0 1 0 4 0 1 1
## EDO 21 465 1 6 3 0 3 23 2 331 4 26 9
## EPE 0 1 13 0 0 0 0 1 0 1 0 0 0
## FAD 0 1 0 96 0 0 1 0 1 1 0 3 0
## FE 0 0 0 0 9 0 0 0 0 0 0 0 0
## FE2 1 0 0 0 1 4 0 0 0 0 0 0 0
## FMN 0 0 1 1 0 0 34 0 0 0 0 1 0
## FMT 1 3 0 0 0 0 0 5 0 5 0 2 0
## GDP 0 0 0 2 0 0 1 0 19 0 0 0 0
## GOL 22 284 7 9 1 0 1 8 4 523 5 29 9
## HEC 0 0 0 0 0 0 0 0 0 0 7 6 0
## HEM 1 4 0 0 0 0 0 2 0 8 14 219 1
## IOD 1 1 0 0 0 0 0 1 0 3 0 0 77
## K 1 0 1 0 0 0 0 1 0 3 0 0 3
## MAN 0 0 0 0 1 0 0 0 0 4 0 1 0
## MES 0 1 3 0 1 0 0 0 0 3 0 2 0
## MG 0 14 0 0 4 0 0 0 0 27 0 2 2
## MLY 0 0 0 0 0 0 0 0 0 1 0 0 0
## MN 0 1 0 0 2 4 1 0 1 0 0 0 1
## MPD 1 3 0 0 0 0 1 1 0 0 0 0 0
## NAD 0 2 1 5 0 0 0 0 0 1 0 0 0
## NAG 1 28 6 22 0 0 11 2 7 79 0 21 1
## NAP 1 2 0 4 0 0 0 0 0 0 0 1 0
## NDP 0 0 0 1 0 0 0 0 0 1 0 0 0
## NI 0 0 0 0 0 1 0 0 0 0 0 0 0
## NO3 2 4 0 0 0 0 1 0 0 0 0 0 0
## PEG 1 5 0 0 0 0 0 1 0 11 0 1 0
## PG4 0 1 0 0 0 0 0 0 0 5 0 1 1
## PGE 0 2 1 0 0 0 0 0 0 1 0 0 1
## PLP 0 0 2 0 0 0 0 0 0 0 0 2 0
## PO4 2 3 0 0 3 0 0 1 0 8 0 4 2
## SAH 0 0 1 0 0 0 1 0 0 0 0 0 0
## SEP 0 2 0 1 0 0 1 0 0 1 0 0 0
## SF4 0 0 0 0 0 0 0 0 1 0 0 0 0
## SO4 74 84 16 6 5 2 4 5 0 134 1 31 29
## TRS 0 0 0 0 0 0 0 0 0 2 0 0 0
## ZN 1 2 2 1 5 15 0 0 0 6 0 3 3
##
## data K MAN MES MG MLY MN MPD NAD NAG NAP NDP NI NO3
## 1PE 0 0 0 0 2 0 0 1 4 0 0 0 0
## ACT 0 1 2 7 2 0 1 1 6 0 2 1 2
## ACY 0 0 0 1 1 0 0 0 0 0 0 1 0
## ADP 0 1 0 1 1 0 0 11 2 4 0 0 0
## ATP 0 1 1 0 0 1 0 2 4 0 1 0 0
## BR 5 0 0 1 0 0 0 0 0 0 0 0 0
## CA 17 2 1 40 3 28 2 0 5 2 2 6 0
## CD 1 0 0 2 0 2 0 0 0 0 0 1 0
## CIT 0 1 0 0 1 1 0 0 0 0 0 0 1
## CL 42 3 1 40 1 8 3 0 14 4 0 4 2
## CLA 0 1 0 0 0 0 0 0 2 0 0 0 0
## COA 0 0 0 0 0 0 0 2 3 0 2 0 0
## CU 0 0 0 1 0 1 0 0 0 0 0 1 0
## DMS 3 0 3 1 0 1 1 0 1 3 0 2 2
## EDO 8 16 15 29 12 3 17 11 52 12 2 0 10
## EPE 1 0 1 2 1 0 0 0 0 0 1 0 0
## FAD 0 0 0 0 0 0 1 7 3 3 5 0 0
## FE 0 0 0 0 0 1 0 0 0 0 0 0 0
## FE2 0 0 1 0 0 0 0 0 0 0 0 0 0
## FMN 0 0 0 0 0 0 0 1 0 3 1 0 0
## FMT 0 0 0 1 0 0 0 0 0 0 0 0 0
## GDP 0 0 0 0 0 0 0 0 0 0 1 0 0
## GOL 6 18 10 58 18 2 30 17 87 9 7 3 6
## HEC 0 0 0 0 0 0 0 0 0 0 0 0 0
## HEM 1 0 1 2 0 0 0 1 3 1 0 0 2
## IOD 2 0 0 0 0 0 0 0 0 0 0 1 0
## K 21 0 0 2 1 0 0 0 2 0 0 0 0
## MAN 1 9 0 0 1 0 0 4 8 0 1 0 0
## MES 0 0 17 0 1 0 1 0 1 0 0 0 0
## MG 3 3 6 191 5 3 0 2 12 2 0 1 1
## MLY 0 0 1 4 9 0 0 0 3 2 1 0 0
## MN 1 0 0 4 0 20 0 0 1 1 0 2 0
## MPD 0 1 0 0 0 1 3 1 2 0 0 0 0
## NAD 0 0 1 1 2 0 0 57 6 13 4 0 0
## NAG 3 24 8 18 10 5 4 17 551 14 8 2 2
## NAP 0 1 0 0 0 0 0 1 1 43 11 0 0
## NDP 0 0 0 0 0 0 0 4 1 4 10 0 0
## NI 0 0 0 0 0 2 0 0 0 0 0 2 0
## NO3 0 0 1 1 0 1 1 0 0 0 0 0 2
## PEG 1 0 0 1 1 2 0 2 5 1 0 1 0
## PG4 0 0 0 1 0 0 0 0 1 0 0 0 1
## PGE 0 0 1 0 0 0 0 1 2 0 0 0 0
## PLP 0 0 0 0 0 1 0 0 0 0 0 0 0
## PO4 2 0 3 6 2 2 2 1 1 2 0 4 1
## SAH 0 0 0 1 0 0 0 3 1 0 0 0 0
## SEP 0 1 0 3 0 0 0 0 1 0 0 1 0
## SF4 0 0 0 0 0 0 0 0 0 0 0 0 0
## SO4 26 9 16 68 12 39 13 3 41 5 8 16 22
## TRS 0 1 0 0 0 0 0 0 0 0 0 0 0
## ZN 1 1 1 10 2 24 1 0 7 1 2 17 1
##
## data PEG PG4 PGE PLP PO4 SAH SEP SF4 SO4 TRS ZN
## 1PE 6 7 3 0 0 0 0 0 4 0 1
## ACT 2 0 0 0 4 0 0 0 10 0 4
## ACY 0 0 0 0 0 0 0 0 3 0 3
## ADP 1 0 0 1 1 2 1 0 3 0 2
## ATP 0 0 0 1 0 2 1 0 0 0 2
## BR 0 0 0 0 0 0 0 0 1 0 1
## CA 0 0 1 0 4 0 1 0 53 0 47
## CD 0 0 0 0 1 0 0 0 4 0 3
## CIT 0 0 0 0 1 0 0 0 3 0 0
## CL 8 2 2 0 10 1 2 2 70 2 12
## CLA 0 0 0 0 0 0 0 0 1 0 1
## COA 0 0 1 1 0 0 0 0 1 0 0
## CU 0 0 0 0 0 0 0 0 0 0 9
## DMS 1 3 0 0 3 0 0 0 22 0 4
## EDO 46 18 13 0 22 4 1 0 100 5 14
## EPE 0 0 0 0 0 1 1 0 1 0 1
## FAD 0 1 0 0 0 0 0 0 2 0 1
## FE 0 0 0 0 0 0 0 0 0 0 1
## FE2 0 0 0 0 0 0 0 0 0 0 1
## FMN 0 0 0 0 0 0 0 0 0 0 0
## FMT 0 0 0 0 0 1 0 0 4 0 0
## GDP 0 0 0 0 1 1 0 0 0 0 0
## GOL 40 24 13 2 21 2 5 0 149 19 23
## HEC 0 0 0 0 1 0 0 0 0 0 0
## HEM 2 0 1 0 3 0 3 0 5 0 2
## IOD 0 0 0 0 3 1 1 0 7 0 4
## K 0 0 0 0 0 0 0 0 2 0 1
## MAN 0 1 0 0 0 0 0 0 2 0 0
## MES 0 0 0 2 0 0 2 0 2 0 0
## MG 0 2 1 0 7 0 0 2 24 8 8
## MLY 1 2 0 0 1 0 0 0 3 0 2
## MN 0 0 0 0 3 0 0 1 5 0 12
## MPD 1 1 0 0 0 0 0 0 1 0 0
## NAD 0 1 0 0 0 1 0 0 5 0 1
## NAG 22 21 8 4 8 9 4 0 25 2 18
## NAP 0 1 0 1 0 0 0 0 0 0 0
## NDP 0 0 0 0 0 0 0 0 0 0 0
## NI 0 0 0 1 0 0 0 0 0 1 2
## NO3 0 0 0 0 0 0 0 0 3 0 1
## PEG 0 5 1 0 2 1 1 0 1 0 1
## PG4 4 4 2 0 0 0 0 0 2 0 1
## PGE 0 0 1 0 0 0 0 0 0 0 0
## PLP 0 0 0 24 2 0 0 0 2 0 3
## PO4 1 0 0 2 25 0 1 0 37 0 2
## SAH 0 0 0 1 0 19 0 0 0 0 0
## SEP 0 0 0 0 0 0 15 0 1 0 2
## SF4 0 0 0 0 0 0 0 52 0 0 0
## SO4 10 3 2 12 195 3 7 0 1220 8 64
## TRS 0 0 0 0 0 0 0 0 0 4 0
## ZN 0 2 0 0 6 0 4 1 16 1 356
##
## Overall Statistics
##
## Accuracy : 0.438
## 95% CI : (0.429, 0.447)
## No Information Rate : 0.1531
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.388
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: 1PE Class: ACT Class: ACY Class: ADP
## Sensitivity 0.1506849 0.126697 0.0270270 0.303922
## Specificity 0.9966515 0.990956 0.9984544 0.995008
## Pos Pred Value 0.2200000 0.212121 0.1000000 0.348315
## Neg Pred Value 0.9946872 0.983345 0.9938462 0.993896
## Prevalence 0.0062287 0.018857 0.0063140 0.008703
## Detection Rate 0.0009386 0.002389 0.0001706 0.002645
## Detection Prevalence 0.0042662 0.011263 0.0017065 0.007594
## Balanced Accuracy 0.5736682 0.558826 0.5127407 0.649465
## Class: ATP Class: BR Class: CA Class: CD Class: CIT
## Sensitivity 0.300000 0.1309524 0.47330 0.227723 0.0943396
## Specificity 0.997425 0.9984531 0.96790 0.997418 0.9990572
## Pos Pred Value 0.411765 0.3793103 0.48094 0.433962 0.3125000
## Neg Pred Value 0.995801 0.9937559 0.96693 0.993314 0.9958988
## Prevalence 0.005973 0.0071672 0.05913 0.008618 0.0045222
## Detection Rate 0.001792 0.0009386 0.02799 0.001962 0.0004266
## Detection Prevalence 0.004352 0.0024744 0.05819 0.004522 0.0013652
## Balanced Accuracy 0.648712 0.5647027 0.72060 0.612570 0.5466984
## Class: CL Class: CLA Class: COA Class: CU Class: DMS
## Sensitivity 0.53468 0.700000 0.042857 0.1369863 0.366255
## Specificity 0.95296 0.999487 0.998712 0.9980252 0.991984
## Pos Pred Value 0.45203 0.777778 0.166667 0.3030303 0.491713
## Neg Pred Value 0.96578 0.999230 0.994274 0.9946094 0.986654
## Prevalence 0.06766 0.002560 0.005973 0.0062287 0.020734
## Detection Rate 0.03618 0.001792 0.000256 0.0008532 0.007594
## Detection Prevalence 0.08003 0.002304 0.001536 0.0028157 0.015444
## Balanced Accuracy 0.74382 0.849743 0.520785 0.5675058 0.679120
## Class: EDO Class: EPE Class: FAD Class: FE Class: FE2
## Sensitivity 0.47112 0.206349 0.607595 0.2250000 0.1176471
## Specificity 0.90478 0.998542 0.996800 0.9994007 0.9996577
## Pos Pred Value 0.31271 0.433333 0.721805 0.5625000 0.5000000
## Neg Pred Value 0.94899 0.995723 0.994649 0.9973513 0.9974385
## Prevalence 0.08422 0.005375 0.013481 0.0034130 0.0029010
## Detection Rate 0.03968 0.001109 0.008191 0.0007679 0.0003413
## Detection Prevalence 0.12688 0.002560 0.011348 0.0013652 0.0006826
## Balanced Accuracy 0.68795 0.602445 0.802197 0.6122003 0.5586524
## Class: FMN Class: FMT Class: GDP Class: GOL
## Sensitivity 0.523077 0.0806452 0.380000 0.41873
## Specificity 0.999056 0.9981987 0.998715 0.88950
## Pos Pred Value 0.755556 0.1923077 0.558824 0.31131
## Neg Pred Value 0.997345 0.9951257 0.997347 0.92769
## Prevalence 0.005546 0.0052901 0.004266 0.10657
## Detection Rate 0.002901 0.0004266 0.001621 0.04462
## Detection Prevalence 0.003840 0.0022184 0.002901 0.14334
## Balanced Accuracy 0.761067 0.5394219 0.689357 0.65412
## Class: HEC Class: HEM Class: IOD Class: K Class: MAN
## Sensitivity 0.2121212 0.58556 0.38119 0.144828 0.0957447
## Specificity 0.9994010 0.99374 0.99522 0.997235 0.9972475
## Pos Pred Value 0.5000000 0.75517 0.58333 0.396226 0.2195122
## Neg Pred Value 0.9977789 0.98644 0.98921 0.989372 0.9927220
## Prevalence 0.0028157 0.03191 0.01724 0.012372 0.0080205
## Detection Rate 0.0005973 0.01869 0.00657 0.001792 0.0007679
## Detection Prevalence 0.0011945 0.02474 0.01126 0.004522 0.0034983
## Balanced Accuracy 0.6057611 0.78965 0.68821 0.571032 0.5464961
## Class: MES Class: MG Class: MLY Class: MN Class: MPD
## Sensitivity 0.186813 0.38431 0.1022727 0.135135 0.037500
## Specificity 0.998108 0.98280 0.9979367 0.995334 0.998540
## Pos Pred Value 0.435897 0.49740 0.2727273 0.270270 0.150000
## Neg Pred Value 0.993665 0.97301 0.9932404 0.989009 0.993419
## Prevalence 0.007765 0.04241 0.0075085 0.012628 0.006826
## Detection Rate 0.001451 0.01630 0.0007679 0.001706 0.000256
## Detection Prevalence 0.003328 0.03276 0.0028157 0.006314 0.001706
## Balanced Accuracy 0.592461 0.68355 0.5501047 0.565234 0.518020
## Class: NAD Class: NAG Class: NAP Class: NDP Class: NI
## Sensitivity 0.380000 0.66146 0.333333 0.1449275 0.0303030
## Specificity 0.995333 0.95279 0.997757 0.9987984 0.9993135
## Pos Pred Value 0.513514 0.51737 0.623188 0.4166667 0.2000000
## Neg Pred Value 0.991989 0.97353 0.992619 0.9949555 0.9945346
## Prevalence 0.012799 0.07108 0.011007 0.0058874 0.0056314
## Detection Rate 0.004863 0.04701 0.003669 0.0008532 0.0001706
## Detection Prevalence 0.009471 0.09087 0.005887 0.0020478 0.0008532
## Balanced Accuracy 0.687666 0.80713 0.665545 0.5718630 0.5148083
## Class: NO3 Class: PEG Class: PG4 Class: PGE
## Sensitivity 0.0363636 0.000000 0.0408163 2.041e-02
## Specificity 0.9986284 0.995421 0.9980210 9.991e-01
## Pos Pred Value 0.1111111 0.000000 0.1481481 9.091e-02
## Neg Pred Value 0.9954709 0.987572 0.9919610 9.959e-01
## Prevalence 0.0046928 0.012372 0.0083618 4.181e-03
## Detection Rate 0.0001706 0.000000 0.0003413 8.532e-05
## Detection Prevalence 0.0015358 0.004522 0.0023038 9.386e-04
## Balanced Accuracy 0.5174960 0.497711 0.5194187 5.098e-01
## Class: PLP Class: PO4 Class: SAH Class: SEP
## Sensitivity 0.461538 0.077160 0.395833 0.300000
## Specificity 0.998800 0.990523 0.998372 0.998372
## Pos Pred Value 0.631579 0.187970 0.500000 0.441176
## Neg Pred Value 0.997603 0.974195 0.997518 0.997005
## Prevalence 0.004437 0.027645 0.004096 0.004266
## Detection Rate 0.002048 0.002133 0.001621 0.001280
## Detection Prevalence 0.003242 0.011348 0.003242 0.002901
## Balanced Accuracy 0.730169 0.533842 0.697103 0.649186
## Class: SF4 Class: SO4 Class: TRS Class: ZN
## Sensitivity 0.896552 0.6800 0.0800000 0.58361
## Specificity 0.999657 0.8647 0.9996572 0.97768
## Pos Pred Value 0.928571 0.4760 0.5000000 0.58940
## Neg Pred Value 0.999486 0.9373 0.9960724 0.97715
## Prevalence 0.004949 0.1531 0.0042662 0.05205
## Detection Rate 0.004437 0.1041 0.0003413 0.03038
## Detection Prevalence 0.004778 0.2187 0.0006826 0.05154
## Balanced Accuracy 0.948104 0.7724 0.5398286 0.78064